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1

Choukroun, D., H. Weiss, I. Y. Bar-Itzhack, and Y. Oshman. "Direction Cosine Matrix Estimation from Vector Observations using a Matrix Kalman Filter." IEEE Transactions on Aerospace and Electronic Systems 46, no. 1 (2010): 61–79. http://dx.doi.org/10.1109/taes.2010.5417148.

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2

Bieda, Robert, and Krzysztof Jaskot. "Determinig of an object orientation in 3D space using direction cosine matrix and non-stationary Kalman filter." Archives of Control Sciences 26, no. 2 (2016): 223–44. http://dx.doi.org/10.1515/acsc-2016-0013.

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Abstract This paper describes a method which determines the parameters of an object orientation in 3D space. The rotation angles calculation bases on the signals fusion obtained from the inertial measurement unit (IMU). The IMU measuring system provides information from a linear acceleration sensors (accelerometers), the Earth’s magnetic field sensors (magnetometers) and the angular velocity sensors (gyroscopes). Information about the object orientation is presented in the form of direction cosine matrix whose elements are observed in the state vector of the non-stationary Kalman filter. The vector components allow to determine the rotation angles (roll, pitch and yaw) associated with the object. The resulting waveforms, for different rotation angles, have no negative attributes associated with the construction and operation of the IMU measuring system. The described solution enables simple, fast and effective implementation of the proposed method in the IMU measuring systems.
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3

Hall, Derek, and Timothy Sands. "Vehicle Directional Cosine Calculation Method." Vehicles 5, no. 1 (2023): 114–32. http://dx.doi.org/10.3390/vehicles5010008.

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Teaching kinematic rotations is a daunting task for even some of the most advanced mathematical minds. However, changing the paradigm can highly simplify envisioning and explaining the three-dimensional rotations. This paradigm change allows a high school student with an understanding of geometry to develop the matrix and explain the rotations at a collegiate level. The proposed method includes the assumption of a point (P) within the initial three-dimensional frame with axes (x^i, y^i, z^i). The method then utilizes a two-dimensional rotation view (2DRV) to measure how the coordinates of point P translate after a rotation around the initial axis. The equations are used in matrix notation to develop a rotation matrix for follow-on direction cosine matrixes. The method removes the requirement to use Euler’s formula, ultimately, providing a high school student with an elementary and repeatable process to compose and explain kinematic rotations, which are critical to attitude direction control systems commonly found in vehicles.
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Zhang, Dong, Yongshun Zhang, and Cunqian Feng. "Enhanced 2D-DOA Estimation for Large Spacing Three-Parallel Uniform Linear Arrays." International Journal of Antennas and Propagation 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/3679494.

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An enhanced two-dimensional direction of arrival (2D-DOA) estimation algorithm for large spacing three-parallel uniform linear arrays (ULAs) is proposed in this paper. Firstly, we use the propagator method (PM) to get the highly accurate but ambiguous estimation of directional cosine. Then, we use the relationship between the directional cosine to eliminate the ambiguity. This algorithm not only can make use of the elements of the three-parallel ULAs but also can utilize the connection between directional cosine to improve the estimation accuracy. Besides, it has satisfied estimation performance when the elevation angle is between 70° and 90° and it can automatically pair the estimated azimuth and elevation angles. Furthermore, it has low complexity without using any eigen value decomposition (EVD) or singular value decompostion (SVD) to the covariance matrix. Simulation results demonstrate the effectiveness of our proposed algorithm.
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5

Kim, Y. V. "Rotation vector and directional cosine matrix in problems of satellite attitude control." International Journal of Aerospace System Science and Engineering 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijasse.2021.10036566.

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6

Kim, Y. V. "Rotation vector and directional cosine matrix in problems of satellite attitude control." International Journal of Intelligent Systems Technologies and Applications 20, no. 5 (2022): 363. http://dx.doi.org/10.1504/ijista.2022.125583.

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7

Ryzhkov, Lev. "Vector methods for determination of rigid body orientation." MECHANICS OF GYROSCOPIC SYSTEMS, no. 41 (December 28, 2022): 102–11. http://dx.doi.org/10.20535/0203-3771412021269249.

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Vector methods for determining the orientation of a rigid body using information about vectors in the reference and body-related coordinate systems are considered. The analysis is based on the least squares method in vector-matrix form. This approach allows us to consider the application of different methods of solving the problem from a single standpoint: matrix (using the directional cosine matrix), geometric (using the Gibbs vector), quaternion (using the quaternion of rotation). Numerical evaluation of the accuracy of eight orientation determination algorithms obtained on the basis of these methods was performed.
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8

Wu, Guoli, Hefeng Dong, Ganpan Ke, and Junqiang Song. "An adapted eigenvalue-based filter for ocean ambient noise processing." GEOPHYSICS 85, no. 1 (2020): KS29—KS38. http://dx.doi.org/10.1190/geo2018-0861.1.

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Accurate approximations of Green’s functions retrieved from the correlations of ambient noise require a homogeneous distribution of random and uncorrelated noise sources. In the real world, the existence of highly coherent, strong directional noise generated by ships, earthquakes, and other human activities can result in biases in the ambient-noise crosscorrelations (NCCs). We have developed an adapted eigenvalue-based filter to attenuate the interference of strong directional sources. The filter is based on the statistical model of the sample covariance matrix and can separate different components of the data covariance matrix in the eigenvalue spectrum. To improve the effectiveness and make it adaptable for different data sets, a weight is introduced to the filter. Then, the NCCs can be calculated directly from the filtered data covariance matrix. This approach is applied to a 1.02 h data set of ambient noise recorded by a permanent reservoir monitoring receiver array installed on the seabed. The power spectral density indicates that the noise recordings were contaminated by strong directional noise over nearly half of the whole observation period. Beamforming and crosscorrelation results indicate that the interference still exists even after applying traditional temporal and spectral normalization techniques, whereas the adapted eigenvalue-based filter can significantly attenuate it and help to obtain improved crosscorrelations. The approach makes it possible to retrieve reliable approximations of Green’s functions over a much shorter recording time.
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9

Lim, SuYeon, MinKyeong Choi, and Yunglyul Lee. "Frequency-Based Adaptive Interpolation Filter in Intra Prediction." Applied Sciences 13, no. 3 (2023): 1475. http://dx.doi.org/10.3390/app13031475.

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This paper proposes a method to improve the fractional interpolation of reference samples in the Versatile Video Coding (VVC) intra prediction. The proposed method uses additional interpolation filters which use more integer-positioned reference samples for prediction according to the frequency information of the reference samples. In VVC, a 4-tap Discrete Cosine Transform-based interpolation filter (DCT-IF) and 4-tap Smoothing interpolation filter (SIF) are alternatively performed on the block size and block directional prediction mode for reference sample interpolation. This paper uses four alternative interpolation filters such as 8-tap/4-tap DCT-IFs, and 4-tap/8-tap SIFs and an interpolation filter selection method using a high-frequency ratio calculated from one-dimensional (1D) transform of the reference samples are proposed. The proposed frequency-based Adaptive Filter allows to achieve the overall Bjøntegaard Delta (BD) rate gains of −0.16%, −0.13%, and −0.09% for Y, Cb, and Cr components, respectively, compared with VVC.
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10

Phuong, Nguyen Ho Quoc, Hee-Jun Kang, Young-Soo Suh, and Young-Sik Ro. "A DCM Based Orientation Estimation Algorithm with an Inertial Measurement Unit and a Magnetic Compass." JUCS - Journal of Universal Computer Science 15, no. (4) (2009): 859–76. https://doi.org/10.3217/jucs-015-04-0859.

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In this paper, Direction Cosine Matrix (DCM) method for attitude and orientation estimation is discussed. DCM method was chosen due to some advantages over the popular methods such as namely Euler Angle, Quaternion in light of reliability, accuracy and computational efforts. Proposed model for each method is developed for methodology comparison. It is shown that normal Kalman Filter in DCM method is better than extended Kalman Filter in Euler and Quaternion based method because it helps avoid the first order approximation error. Methodology errors are verified using Aerospace Blockset of Matlab Simulink.
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11

Oliveira Filho, Milton E. de, Alfeu J. Sguarezi Filho, and Ernesto Ruppert. "A Three-phase to three-phase matrix converter prototype." Sba: Controle & Automação Sociedade Brasileira de Automatica 23, no. 3 (2012): 247–62. http://dx.doi.org/10.1590/s0103-17592012000300001.

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This paper presents some implementation details of a three-phase to three-phase matrix converter prototype. The bidirectional semiconductor switches were built using discrete IGBTs and fast diodes. Design aspects such as protection against overvoltage and short-circuit, commutation process of bi-directional switches, and input filter are addressed in this paper.
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12

Berbar, MohammedA, Awatif Alqahtani, and Muhammad Hussain. "Masses Classification Using Discrete Cosine Transform and Wavelet-Based Directional Filter Bank for Breast Cancer Diagnosis." Journal of Medical Imaging and Health Informatics 6, no. 1 (2016): 117–24. http://dx.doi.org/10.1166/jmihi.2016.1599.

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13

Liu, Shao Peng, Zhao Ying Zhou, Qiong Wang, Qi Guo, and Zhi Guang Ma. "A Micro Wireless Attitude Determination System Based on the Extended Kalman Filter." Advanced Materials Research 328-330 (September 2011): 2274–77. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.2274.

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One wireless attitude measurement system based on a MEMS multi-sensor has been developed. The data from 3-axis MEMS accelerators and 3-axis MEMS gyroscopes are used to determine the pitch angle and the roll angle by using an extended Kalman filter (EKF) equation deduced from the direction cosine matrix. The attitude angles can be resolved from the EKF algorithm based on Quaternion. The system can be used in dynamic as well as static environments by adjusting the measurement noise matrix of the extended Kalman filter equation. Results indicate that system is determined with standard deviations below 5º even in high dynamics and 1º in static state. The system can collect wireless data from over six nodes simultaneously with a sampling rate up to 100 Hz. The system node measuring 22x15x10mm and weighing 4.5g contains wireless communication module, 3-axis gyroscope, magnetometer and accelerometer.
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14

Liu, Lijun, Chang Yin, Yonghui Su, Yinghai Lin, and Ying Lei. "Optimization of Covariance Matrices of Kalman Filter with Unknown Input Using Modified Directional Bat Algorithm." Buildings 15, no. 2 (2025): 196. https://doi.org/10.3390/buildings15020196.

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The proper selection of the model error covariance matrix and the measurement noise covariance matrix of Kalman filter is an optimization problem. Some scholars have studied this, but there is relatively little research on the selection of the two covariance matrices for Kalman filters with an unknown input. Recently, the authors proposed a modified directed bat algorithm (MDBA) which introduces the best historical location of individuals and the elimination strategy to effectively prevent falling into local optimal solution. So, two methods are proposed in this paper to optimize the model error covariance matrix and measurement noise covariance matrix of Kalman filter with unknown inputs (KF-UI) and extended Kalman filter with unknown inputs (EKF-UI) by MDBA, respectively. The objective functions are constructed using the measurement vectors and the corresponding estimated values, and MDBA is adopted to optimize the two covariance matrices of KF-UI and EKF-UI. To validate the effectiveness of proposed methods, two simple structure examples and a benchmark example are adopted. The influence of structural parameter uncertainties on KF-UI is also considered. The result shows that the MDBA-optimized KF-UI has a strong convergence and can take into account the effect of parameter uncertainties. Then, the effectiveness of the proposed MDBA-optimized EKF-UI method is validated by comparing it with EKF-UI with empirically selected covariance values through trial-and-error. The identification results showed that the proposed methods achieved better identification accuracy and enhanced convergence compared to KF-UI and EKF-UI with empirical covariance values.
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15

Svinkunas, Gytis, and Gytis Petrauskas. "Switching Ripple Harmonics Attenuation in DFIG and Matrix Converter-Based WECS." Electronics 10, no. 21 (2021): 2589. http://dx.doi.org/10.3390/electronics10212589.

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The analysis presented in this paper is focused on the harmonics distortion damping in the case of bidirectional power-flow of the electronics device—matrix converter as an interface between two power sources. Bidirectional energy flow takes place in the matrix converter that is used in renewables, hybrid transformers, microgrids, etc. It is observed that the matrix converter generates sinusoidal voltage with some amount of harmonic distortion and worsens in the quality of power in the utility grid. Taking into account the bi-directional energy flow and the matrix converter operation principle, four key requirements for the filters are formulated. Six theoretically possible filter topologies are investigated for compliance with these requirements. Two of the filter topologies are recognized as complying with these requirements and applicable for the switching ripple harmonics damping in the utility grid connected matrix converter in the case of bidirectional power flow. The suitability of these topologies was verified by MATLAB/Simulink simulation. Using the proper filter topology will significantly reduce the size, weight and cost of the components of the filter, as well as the utility grid’s pollution by switching ripple harmonics. It is appropriate to apply such filters to matrix converters that operate in wind turbines installed in doubly fed induction generators. These filters should also be used in hybrid transformers and other high-power devices with matrix converters.
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16

Yu, Xiaoyan, Chengyou Wang, and Xiao Zhou. "A Robust Color Image Watermarking Algorithm Based on APDCBT and SSVD." Symmetry 11, no. 10 (2019): 1227. http://dx.doi.org/10.3390/sym11101227.

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With the wide application of color images, watermarking for the copyright protection of color images has become a research hotspot. In this paper, a robust color image watermarking algorithm based on all phase discrete cosine biorthogonal transform (APDCBT) and shuffled singular value decomposition (SSVD) is proposed. The host image is transformed by the 8 × 8 APDCBT to obtain the direct current (DC) coefficient matrix, and then, the singular value decomposition (SVD) is performed on the DC matrix to embed the watermark. The SSVD and Fibonacci transform are mainly used at the watermark preprocessing stage to improve the security and robustness of the algorithm. The watermarks are color images, and a color quick response (QR) code with error correction mechanism is introduced to be a watermark to further improve the robustness. The watermark embedding and extraction processes are symmetrical. The experimental results show that the algorithm can effectively resist common image processing attacks, such as JPEG compression, Gaussian noise, salt and pepper noise, average filter, median filter, Gaussian filter, sharpening, scaling attacks, and a certain degree of rotation attacks. Compared with the color image watermarking algorithms considered in this paper, the proposed algorithm has better performance in robustness and imperceptibility.
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17

Alves, Fabio, and Justin Ivancic. "Narrowband underwater vector sensor using michroelectromechanical systems." Journal of the Acoustical Society of America 154, no. 4_supplement (2023): A210. http://dx.doi.org/10.1121/10.0023306.

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A narrowband underwater vector sensor using microelectromechanical (MEMS) systems is demonstrated. A combination of two pressure gradient MEMS sensors and an omnidirectional hydrophone allows for determination of the direction of arrival (DOA) of income sound over 360 degrees azimuth. The MEMS sensors, inspired on the hearing system of the Ormia-ochracea fly, consist of two wings connected by a bridge and anchored to the substrate by a tortional bean. They are operated with open back to allow a cosine dependence with the angle of incidence in the predominant bending vibrational mode. In the vector sensor, two MEMS sensors are orthogonally arranged to provide a cosine and sine directional pattern. When combined with an omnidirectional hydrophone that shares the same phase center, an arctangent estimator is used for DOA determination. The MEMS sensors are operated near resonance to filter out noise coming from undesired bands and improve the signal-to-noise ratio. A correction algorithm is applied to compensate frequency response differences. Two configurations have been demonstrated with the MEMS sensors enclosed in silicone oil and in air. The standard deviation of the measured DOA error has been computed for both configurations to be less than 5 degrees for various types of sound stimuli.
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18

Liang, Lili, and Han Liu. "Dual-Tree Cosine-Modulated Filter Bank With Linear-Phase Individual Filters: An Alternative Shift-Invariant and Directional-Selective Transform." IEEE Transactions on Image Processing 22, no. 12 (2013): 5168–80. http://dx.doi.org/10.1109/tip.2013.2283146.

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19

Swamy, K. Ayyappa, and Zachariah C. Alex. "Efficient hearing aid algorithm using DCT with uniformly re-sampled and recursively modified audiogram values." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (2021): 237. http://dx.doi.org/10.11591/ijeecs.v23.i1.pp237-246.

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People with the hearing problems have different listening preferences and characteristics in hearing loss. So, hearing aids need algorithms that provide amplification based on frequency, so that the hearing-impaired persons can use hearing aids comfortably for a long duration. In this paper, a new algorithm is proposed for hearing aids in order to compensate for sensorineural and conductive hearing loss using discrete cosine transform (DCT). DCT coefficients of the input audio signal are multiplied with uniformly resampled and recursively modified audiogram values to compensate for hearing loss. This algorithm comprised of 4 stages namely precomputation to calculate gain values from audiogram, DCT, gain adjustment, and inverse DCT. In the above stated stages except precomputation, each stage requires only one matrix multiplication, which makes the proposed algorithm computational efficient. Performance of the proposed algorithm is compared with uniform filter banks, non-uniform filter banks, variable filter bank and reconfigurable filter banks. The algorithm is tested using audiograms with four different hearing loss cases. It is proved that the proposed algorithm provides less complexity, minimized delay and better matching with all types of audiograms, further, it also avoids degradation of audio signal due to sampling rate conversions in variable and reconfigurable filter banks.
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20

Swamy, K. Ayyappa, and Zachariah C. Alex. "Efficient hearing aid algorithm using DCT with uniformly re-sampled and recursively modified audiogram values." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (2021): 237–46. https://doi.org/10.11591/ijeecs.v23.i1.pp237-246.

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People with the hearing problems have different listening preferences and characteristics in hearing loss. So, hearing aids need algorithms that provide amplification based on frequency, so that the hearing-impaired persons can use hearing aids comfortably for a long duration. In this paper, a new algorithm is proposed for hearing aids in order to compensate for sensorineural and conductive hearing loss using discrete cosine transform (DCT). DCT coefficients of the input audio signal are multiplied with uniformly resampled and recursively modified audiogram values to compensate for hearing loss. This algorithm comprised of 4 stages namely precomputation to calculate gain values from audiogram, DCT, gain adjustment, and inverse DCT. In the above stated stages except precomputation, each stage requires only one matrix multiplication, which makes the proposed algorithm computational efficient. Performance of the proposed algorithm is compared with uniform filter banks, non-uniform filter banks, variable filter bank and reconfigurable filter banks. The algorithm is tested using audiograms with four different hearing loss cases. It is proved that the proposed algorithm provides less complexity, minimized delay and better matching with all types of audiograms, further, it also avoids degradation of audio signal due to sampling rate conversions in variable and reconfigurable filter banks.
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21

Zhang, Guanming, and Yang Lu. "Quantifying Anisotropic Properties of Old–New Concrete Interfaces Using X-Ray Computed Tomography and Homogenization." Infrastructures 10, no. 1 (2025): 20. https://doi.org/10.3390/infrastructures10010020.

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The interface between old and new concrete is a critical component in many construction practices, including concrete pavements, bridge decks, hydraulic dams, and buildings undergoing rehabilitation. Despite various treatments to enhance bonding, this interface often remains a weak layer that compromises overall structural performance. Traditional design methods typically oversimplify the interface as a homogeneous or empirically adjusted factor, resulting in significant uncertainties. This paper introduces a novel framework for quantifying the anisotropic properties of old–new concrete interfaces using X-ray computed tomography (CT) and finite element-based numerical homogenization. The elastic coefficient matrix reveals that specimens away from the interface exhibit higher values in both normal and shear directions, with normal direction values averaging 33.15% higher and shear direction values 39.96% higher than those at the interface. A total of 10 sampling units along the interface were collected and analyzed to identify the “weakest vectors” in normal and shear directions. The “weakest vectors” at the interface show consistent orientations with an average cosine similarity of 0.62, compared with an average cosine similarity of 0.23 at the non-interface, which demonstrates directional features. Conversely, the result of average cosine similarity at the interface shows randomness that originates from the anisotropy of materials. The average angle between normal and shear stresses was found to be 88.64°, indicating a predominantly orthogonal relationship, though local stress distributions introduced slight deviations. These findings highlight the importance of understanding the anisotropic properties of old–new concrete interfaces to improve design and rehabilitation practices in concrete and structural engineering.
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22

Khan, Mohammad A. U., and Tariq M. Khan. "Calibrating second-moment matrix for better shape adaptation with bias term from directional filter bank." Signal, Image and Video Processing 11, no. 8 (2017): 1453–60. http://dx.doi.org/10.1007/s11760-017-1107-6.

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23

Wang, Jin Tao, Yong Quan Lu, Chu Qiu, Peng Dong Gao, Jie Fu, and Wen Hua Yu. "Research on Setting Parameter of Deblocking Filter for H.264." Applied Mechanics and Materials 20-23 (January 2010): 70–75. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.70.

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The emerging coding standard H.264 is mainly intended for video transmission in many areas. Considering the peculiarity of blocking artifacts which results from block based transform using DCT (discrete cosine transform ) that is most popular method for video coding. These blocking which is due to deficiency of correlation between blocks has much troublesome impact at low bit rate encoding. In this paper, we analyzed the performance of common deblocking filter within H.264 standard, investigated the principle of parameter setting for deblocking filter in an open source code(x264). The outputs of deblocking filter depend on the boundary strength parameter “BS” and the gradient of image samples across the boundary [1]. Usually the filter parameters αc and β were specified a default value zero during x264 running, but in fact selecting different values have a significant effect in the view of image quality. The two statistical parameters of Gray Level co-occurrence Matrix (GLCM), energy and entropy, were used to evaluate the texture of each video picture, and then specify appropriate values for the filter parameters αc and β. We may appraise the effect of deblocking in terms of calculating Mean Squared Difference of Slope (MSDS) for each video frame. In the end of this paper, the experimental results show that our approach, comparing with existing deblocking techniques, is one of the significant methods for reducing blocking artifacts.
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RENDRAGRAHA, RENDY DWI, GELAR BUDIMAN, and IRMA SAFITRI. "QIM - Based Audio Watermarking with Combination Technique of DCT-QR-CPT." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 7, no. 1 (2019): 112. http://dx.doi.org/10.26760/elkomika.v7i1.112.

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ABSTRAKAudio watermarking adalah teknik memasukkan informasi ke dalam file audio dan untuk melindungi hak cipta data digital dari distribusi ilegal. Makalah ini memperkenalkan audio stereo watermarking berdasarkan Quantization Index Modulation (QIM) dengan teknik gabungan Discrete Cosine Transform (DCT) - QRCartesian Polar Transform (CPT). Host audio dibagi menjadi beberapa frame, selanjutnya setiap frame ditransformasi oleh DCT, kemudian output DCT diuraikan menjadi matriks orthogonal dan matriks segitiga menggunakan metode QR. Selanjutnya, CPT mengubah dua koefisien kartesian dari matriks segitiga (R) pada posisi (1,1) dan (2,2) menjadi koefisien polar. Setelah itu, penyisipan dilakukan pada koefisien polar oleh QIM. Hasil simulasi menunjukkan bahwa imperseptibilitas audio terwatermark berkualitas baik dengan Signal to Noise Ratio (SNR)> 20, Mean Opinion Score (MOS)> 4 dan tahan terhadap serangan seperti Low Pass Filter (LPF) dan Band Pass Filter (BPF) dengan cut off 25-6k, resampling, Linear Speed Change (LSC) dan MP3 Compression dengan rate diatas 64 kbps.Kata kunci: Audio Watermarking, CPT, DCT, QIM, QR ABSTRACTAudio watermarking is a technique for inserting information into an audio file and to protect the copyright of digital data from illegal distribution. This paper introduces a stereo audio watermarking based on Quantization Index Modulation (QIM) with combined technique Discrete Cosine Transform (DCT) – QR – Cartesian Polar Transform (CPT). Each frame of a host audio is transformed by DCT, then DCT output is decomposed using QR method. Next, CPT transform two cartesian coefficients from triangular matrix (R) in position (1,1) and (2,2) to polar coefficients. After that, embedding is executed on polar coefficients by QIM. The simulation result shows that the imperceptibility is good with Signal to Noise Ratio (SNR)>20, Mean Opinion Score (MOS)>4 and it is robust against attacks such as Low Pass Filter (LPF) and Band Pass Filter (BPF) with cut off 25-6k, Resampling, Linear Speed Change and MP3 Compression with rate 64 kbps and above. Keywords: Audio Watermarking, CPT, DCT, QIM, QR
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Ali, Musrrat, and Sanoj Kumar. "A Robust Zero-Watermarking Scheme in Spatial Domain by Achieving Features Similar to Frequency Domain." Electronics 13, no. 2 (2024): 435. http://dx.doi.org/10.3390/electronics13020435.

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In recent years, there has been a substantial surge in the application of image watermarking, which has evolved into an essential tool for identifying multimedia material, ensuring security, and protecting copyright. Singular value decomposition (SVD) and discrete cosine transform (DCT) are widely utilized in digital image watermarking despite the considerable computational burden they involve. By combining block-based direct current (DC) values with matrix norm, this research article presents a novel, robust zero-watermarking approach. It generates a zero-watermark without attempting to modify the contents of the image. The image is partitioned into non-overlapping blocks, and DC values are computed without applying DCT. This sub-image is further partitioned into non-overlapping blocks, and the maximum singular value of each block is calculated by matrix norm instead of SVD to obtain the binary feature matrix. A piecewise linear chaotic map encryption technique is utilized to improve the security of the watermark image. After that, the feature image is created via XOR procedure between the encrypted watermark image and the binary feature matrix. The proposed scheme is tested using a variety of distortion attacks including noise, filter, geometric, and compression attacks. It is also compared with the other relevant image watermarking methods and outperformed them in most cases.
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26

Musa, P., I. Purwanto, D. A. Christie, E. P. Wibowo, and R. Irawan. "The methodology for obtaining nonlinear and continuous three-dimensional topographic data using inertial and optical measuring instruments of unmanned ground systems." Computer Optics 46, no. 2 (2022): 280–97. http://dx.doi.org/10.18287/2412-6179-co-915.

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Topography is the study of an area on the earth's surface. This term relates to the land's slope or contour, which is the interval of elevation differences between two adjacent and parallel contour lines. Topography generally presents a three-dimensional model of object surface relief and an identification of land or hilly areas based on horizontal coordinates such as latitude and longitude, and vertical position, namely elevation. The topography is essential information that must be provided in the execution of building or road construction based on the ground contour. The problem which is the ground contour which can provide visualization topography as a three-dimensional (3D) condition of the ground contour is not normal (non-linear). Another problem is that the traditional measurement techniques with wheel rotation only measure distances and cannot represent the trajectory of the ground contour in 3D. The proposed in-depth evaluation of orientation estimation results in the topography accuracy level. This methodology consists of several processes; Inertia and orientation of an object, Distance measurement, Terrestrial topocentric – Euclidean transformation, and Topography visualization. This research designed a prototype and proposed a new visualization method of the ground contours to reconstruct a topography map between three algorithms; Direct Cosine Matrix-3D Coordinate, Madgwick-3D Coordinate, and Complementary Filter. The methodology was tested and evaluated intensively by direct observation at three measurement locations with different difficulty levels. As a result, the Direct Cosine Matrix-3D Coordinate is able to visualize the ground contours by reconstructing a topography map much better than other methods.
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27

Musa, P., I. Purwanto, D. A. Christie, E. P. Wibowo, and R. Irawan. "The methodology for obtaining nonlinear and continuous three-dimensional topographic data using inertial and optical measuring instruments of unmanned ground systems." Computer Optics 46, no. 2 (2022): 280–97. http://dx.doi.org/10.18287/2412-6179-co-915.

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Topography is the study of an area on the earth's surface. This term relates to the land's slope or contour, which is the interval of elevation differences between two adjacent and parallel contour lines. Topography generally presents a three-dimensional model of object surface relief and an identification of land or hilly areas based on horizontal coordinates such as latitude and longitude, and vertical position, namely elevation. The topography is essential information that must be provided in the execution of building or road construction based on the ground contour. The problem which is the ground contour which can provide visualization topography as a three-dimensional (3D) condition of the ground contour is not normal (non-linear). Another problem is that the traditional measurement techniques with wheel rotation only measure distances and cannot represent the trajectory of the ground contour in 3D. The proposed in-depth evaluation of orientation estimation results in the topography accuracy level. This methodology consists of several processes; Inertia and orientation of an object, Distance measurement, Terrestrial topocentric – Euclidean transformation, and Topography visualization. This research designed a prototype and proposed a new visualization method of the ground contours to reconstruct a topography map between three algorithms; Direct Cosine Matrix-3D Coordinate, Madgwick-3D Coordinate, and Complementary Filter. The methodology was tested and evaluated intensively by direct observation at three measurement locations with different difficulty levels. As a result, the Direct Cosine Matrix-3D Coordinate is able to visualize the ground contours by reconstructing a topography map much better than other methods.
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Ye, Dan, Yue Long, and Guang-Hong Yang. "Finite-Frequency Filter Design for Networked Control Systems with Missing Measurements." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/825143.

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This paper is concerned with the problem of robust filter design for networked control systems (NCSs) with random missing measurements. Different from existing robust filters, the proposed one is designed in finite-frequency domain. With consideration of possible missing data, the NCSs are first modeled to Markov jump systems (MJSs). A finite-frequency stochasticH∞performance is subsequently given that extends the standardH∞performance, and then a sufficient condition guaranteeing the system to be with such a performance is derived in terms of linear matrix inequality (LMI). With the aid of this condition, a procedure of filter synthesis is proposed to deal with noises in the low-, middle-, and high-frequency domains, respectively. Finally, an example about the lateral-directional dynamic model of the NASA High Alpha Research Vehicle (HARV) is carried out to illustrate the effectiveness of the proposed method.
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Kasula, Pavithra, James F. Whidborne, and Zeeshan A. Rana. "Quaternion-Based Attitude Estimation of an Aircraft Model Using Computer Vision." Sensors 24, no. 12 (2024): 3795. http://dx.doi.org/10.3390/s24123795.

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Investigating aircraft flight dynamics often requires dynamic wind tunnel testing. This paper proposes a non-contact, off-board instrumentation method using vision-based techniques. The method utilises a sequential process of Harris corner detection, Kanade–Lucas–Tomasi tracking, and quaternions to identify the Euler angles from a pair of cameras, one with a side view and the other with a top view. The method validation involves simulating a 3D CAD model for rotational motion with a single degree-of-freedom. The numerical analysis quantifies the results, while the proposed approach is analysed analytically. This approach results in a 45.41% enhancement in accuracy over an earlier direction cosine matrix method. Specifically, the quaternion-based method achieves root mean square errors of 0.0101 rad/s, 0.0361 rad/s, and 0.0036 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. Notably, the method exhibits a 98.08% accuracy for the pitch rate. These results highlight the performance of quaternion-based attitude estimation in dynamic wind tunnel testing. Furthermore, an extended Kalman filter is applied to integrate the generated on-board instrumentation data (inertial measurement unit, potentiometer gimbal) and the results of the proposed vision-based method. The extended Kalman filter state estimation achieves root mean square errors of 0.0090 rad/s, 0.0262 rad/s, and 0.0034 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. This method exhibits an improved accuracy of 98.61% for the estimation of pitch rate, indicating its higher efficiency over the standalone implementation of the direction cosine method for dynamic wind tunnel testing.
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Liu, Li, Wang, and Zhang. "An Adaptive UWB/MEMS-IMU Complementary Kalman Filter for Indoor Location in NLOS Environment." Remote Sensing 11, no. 22 (2019): 2628. http://dx.doi.org/10.3390/rs11222628.

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High precision positioning of UWB (ultra-wideband) in NLOS (non-line-of-sight) environment is one of the hot issues in the direction of indoor positioning. In this paper, a method of using a complementary Kalman filter (CKF) to fuse and filter UWB and IMU (inertial measurement unit) data and track the errors of variables such as position, speed, and direction is presented. Based on the uncertainty of magnetometer and acceleration, the noise covariance matrix of magnetometer and accelerometer is calculated dynamically, and then the weight of magnetometer data is set adaptively to correct the directional error of gyroscope. Based on the uncertainty of UWB distance observations, the covariance matrix of UWB measurement noise is calculated dynamically, and then the weight of UWB data observations is set adaptively to correct the position error. The position, velocity and direction errors are corrected by the fusion of UWB and IMU. The experimental results show that the algorithm can reduce the gyroscope deviation with magnetic noise and motion noise, so that the orientation estimates can be improved, as well as the positioning accuracy can be increased with UWB ranging noise.
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Salman, Mohammad Shukri, Alaa Eleyan, and Bahaa Al-Sheikh. "Discrete wavelet transform-based RI adaptive algorithm for system identification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2383. http://dx.doi.org/10.11591/ijece.v10i3.pp2383-2391.

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In this paper, we propose a new adaptive filtering algorithm for system identification. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCTLMS), discrete-wavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
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Mohammad, Shukri Salman, Eleyan Alaa, and Al-Sheikh Bahaa. "Discrete wavelet transform-based RI adaptive algorithm for system identification." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 2383–91. https://doi.org/10.11591/ijece.v10i3.pp2383-2391.

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In this paper, we propose a new adaptive filtering algorithm for system identification. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCT-LMS), discrete wavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
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Hyyti, Heikki, and Arto Visala. "A DCM Based Attitude Estimation Algorithm for Low-Cost MEMS IMUs." International Journal of Navigation and Observation 2015 (November 30, 2015): 1–18. http://dx.doi.org/10.1155/2015/503814.

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An attitude estimation algorithm is developed using an adaptive extended Kalman filter for low-cost microelectromechanical-system (MEMS) triaxial accelerometers and gyroscopes, that is, inertial measurement units (IMUs). Although these MEMS sensors are relatively cheap, they give more inaccurate measurements than conventional high-quality gyroscopes and accelerometers. To be able to use these low-cost MEMS sensors with precision in all situations, a novel attitude estimation algorithm is proposed for fusing triaxial gyroscope and accelerometer measurements. An extended Kalman filter is implemented to estimate attitude in direction cosine matrix (DCM) formation and to calibrate gyroscope biases online. We use a variable measurement covariance for acceleration measurements to ensure robustness against temporary nongravitational accelerations, which usually induce errors when estimating attitude with ordinary algorithms. The proposed algorithm enables accurate gyroscope online calibration by using only a triaxial gyroscope and accelerometer. It outperforms comparable state-of-the-art algorithms in those cases when there are either biases in the gyroscope measurements or large temporary nongravitational accelerations present. A low-cost, temperature-based calibration method is also discussed for initially calibrating gyroscope and acceleration sensors. An open source implementation of the algorithm is also available.
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Cai, Zhen, Xuzhi Lai, Min Wu, Chengda Lu, and Luefeng Chen. "Trajectory Azimuth Control Based on Equivalent Input Disturbance Approach for Directional Drilling Process." Journal of Advanced Computational Intelligence and Intelligent Informatics 25, no. 1 (2021): 31–39. http://dx.doi.org/10.20965/jaciii.2021.p0031.

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This paper concerns with trajectory azimuth control in directional drilling. The motion process of the drill bit and a series of stabilizers are described, and a state-space model of the trajectory azimuth is constructed. The scheme of the trajectory azimuth control system is designed based on the equivalent input disturbance approach. An internal model is inserted to track the drill bit to improve the quality of the drilling trajectory. A state observer is combined with a low-pass filter to estimate the trajectory azimuth by measuring the azimuth of the bottom hole assembly (BHA). The control parameters can be obtained by the condition of system stability, which is derived in terms of linear matrix inequalities. A typical case is used to illustrate the validity and robustness of our approach.
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Ishaq, Muhammad, Yanbo Che, and Kifayat Ullah. "Switching Regulation in the Control of 5-Phase Permanent Magnet Synchronous Motor Fed by 3×5 Direct Matrix Converter." European Journal of Electrical Engineering 23, no. 1 (2021): 27–35. http://dx.doi.org/10.18280/ejee.230104.

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Matrix converter is an AC-AC direct power converter comprising of an array of bi-directional switches. It does not require an intermediate DC-link and allows sinusoidal output waveforms with varying amplitudes and frequencies. The configuration of these bi-directional switches decides the number of inputs and outputs of the matrix converter. This research uses a direct matrix converter (DMC) as a phase-changing device that can convert a three-phase AC voltage into a 5-phase AC voltage. The DMC is modulated with the model predictive control algorithm. The output of DMC is fed to a five-phase permanent magnet synchronous motor (PMSM). The model predictive current control technique for DMC is carried out by developing a mathematical model of an input filter and PM motor used as a load. The predictive control of DMC results in sinusoidal output current, and it also enables the frequency variation in the output current. This frequency variation is useful in controlling the speed of the motor connected to the load. After controlling the 5-phase motor, the switching frequency regulation is done to observe its effect on the motor's stator current waveforms. Switching frequency regulation helps to limit the unnecessary switching of DMC. We developed a MATLAB-based Simulink model to study PMSM, and detailed results are presented. The results show that switching regulation can significantly reduce the switching frequency without compromising the current waveform quality.
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Blanza, Jojo. "Wireless Propagation Multipaths using Spectral Clustering and Three-Constraint Affinity Matrix Spectral Clustering." Baghdad Science Journal 18, no. 2(Suppl.) (2021): 1001. http://dx.doi.org/10.21123/bsj.2021.18.2(suppl.).1001.

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This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise Jaccard index of the membership of the multipaths to their clusters. The multipaths generated by C2CM were transformed using the directional cosine transform (DCT) and the whitening transform (WT). The transformed dataset was clustered using SC and 3CAM-SC. The clustering performance was validated using the Jaccard index by comparing the reference multipath dataset with the calculated multipath clusters. The results show that the effectiveness of SC is similar to the state-of-the-art clustering approaches. However, 3CAM-SC outperforms SC in all channel scenarios. SC can be used in indoor scenarios based on accuracy, while 3CAM-SC is applicable in indoor and semi-urban scenarios. Thus, the clustering approaches can be applied as alternative clustering techniques in the field of channel modeling.
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Zhao, Xiaodong, Jianzhong Cao, Zuofeng Zhou, and Jijiang Huang. "A Novel PDE-Based Single Image Super-Resolution Reconstruction Method." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 06 (2017): 1754010. http://dx.doi.org/10.1142/s0218001417540106.

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For applications such as remote sensing imaging and medical imaging, high-resolution (HR) images are urgently required. Image Super-Resolution (SR) reconstruction has great application prospects in optical imaging. In this paper, we propose a novel unified Partial Differential Equation (PDE)-based method to single image SR reconstruction. Firstly, two directional diffusion terms calculated by Anisotropic Nonlinear Structure Tensor (ANLST) are constructed, combing information of all channels to prevent singular results, making full use of its directional diffusion feature. Secondly, by introducing multiple orientations estimation using high order matrix-valued tensor instead of gradient, orientations can be estimated more precisely for junctions or corners. As a unique descriptor of orientations, mixed orientation parameter (MOP) is separated into two orientations by finding roots of a second-order polynomial in the nonlinear part. Then, we synthesize a Gradient Vector Flow (GVF) shock filter to balance edge enhancement and de-noising process. Experimental results confirm the validity of the method and show that the method enhances image edges, restores corners or junctions, and suppresses noise robustness, which is competitive with the existing methods.
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Ushida, Jun, Tadashi Murao, Akemi Shiina, and Tsuyoshi Horikawa. "Systematic identification of crosstalk and bandwidth upper limit in highly cascaded Mach–Zehnder lattice optical filters." Japanese Journal of Applied Physics 61, no. 2 (2022): 022001. http://dx.doi.org/10.35848/1347-4065/ac43ce.

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Abstract Crosstalk among channels in wavelength division multiplexing (WDM) filters must be suppressed to enhance receiver sensitivity in direct-detection-based optical communication systems. We present a systematic method to identify the maximum crosstalk and upper limit of the transmission spectrum bandwidth of a highly multi-staged Mach–Zehnder interference (MZI) lattice optical filter with a number of cascade N(N = 1, 2, ⋯ ∞). The scattering matrix including the wafer-level-measurement-based coupling coefficients of directional couplers is used to calculate the transmittance from the input to each output channel and the result is exactly extrapolated to infinite N. This method can be used to design, characterize, and evaluate N-cascaded MZI lattice optical filters that must meet strict WDM specifications.
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Shevtsov, Kostiantyn, and Ilya Galitskiy. "MODELING OF BANDPASS FILTERS WITH ATTENUATION POLES USING PARALLEL COUPLING CHANNELS." Information and Telecommunication Sciences, no. 2 (December 23, 2024): 53–67. https://doi.org/10.20535/2411-2976.22024.53-67.

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Background. Microwave filters are critical components in modern communication systems, playing a fundamental role in signal processing by allowing specific frequency bands to pass while attenuating unwanted frequencies. Over the years, significant advancements have been made in the design and development of various types of microwave filters, including directional, microstrip, and multi-resonator filters. These filters are widely used in radar, satellite communications, and wireless networks, where high performance and precise frequency control are essential. Objective. This paper is dedicated to reviewing various microwave filters that were constructed developed or analysed by the team, including directional filters, microstrip filters with attenuation poles, and multi-resonator filters. The studies focus on investigating their unique properties, such as the formation of attenuation poles, metamaterial characteristics, and the effects of resonator coupling on filter performance. New Python-based software realization for modelling different filters six resonators, four resonators, and two resonators were developed and frequently used. Methods. Electrodynamics simulations using software tools like CST Studio Suite, AWR Microwave Office, and LabVIEW, modelling filters using equivalent circuit models and bridge circuits. Use of microstrip lines, circular resonators, and dielectric resonators to construct and analyse different filter configurations. Analysis of energy propagation paths, resonator coupling, and transmission characteristics to optimize filter design. Results: Various structures were researched like Microwave Directional Filters, Microstrip Resonator Filters with 2, 4, 6 resonator, their structures and characteristics were analysed, New python-based software that allows modelling resonance curves using corresponding parameters for filters with 2, 4, 6 resonators. The parameters of the scattering matrix of a bridge quadrupole were expressed in an analytical form and were used for Python based program. Conclusions: the research presented across these publications contributes significantly to the development and understanding of advanced microwave filter designs. The article reveals various resonator-based filters, including directional, microstrip, and multi-resonator filters, these studies have highlighted key performance enhancements achievable through resonator coupling, metamaterial properties, and the introduction of attenuation poles. The use of advanced simulation tools, such as CST Studio Suite, AWR Microwave Office, and LabVIEW, allowed for accurate modelling and validation of theoretical designs. The introduction of Fano resonances and trapped modes in filters demonstrated improvements in selectivity and attenuation characteristics, which are critical for modern communication systems. Trapped modes manifest as attenuation poles, resulting from the interference of even and odd oscillations. This is evidenced by the presence of two independent energy pathways, along which these interfering oscillations propagate. With appropriate design parameters (such as resonator coupling coefficients and resonance frequencies), a complete energy exchange between resonators can occur at a certain frequency, in a direction perpendicular to the primary energy flow from input to output. The design and properties of directional filters based on circular resonators and dielectric resonators were described. These filters have "metamaterial" properties and are widely used in modern microwave technology. The characteristics of bandpass and rejector filters, as well as the characteristics of the filters formed by two microstrip resonators and resonators connected to each other, are given. It is important to emphasize the phenomena of "Fano resonances" observed in these filters, which arise as the interference of oscillations from individual resonators.
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Luo, Jing, Dan Song, Chunbo Xiu, Shuze Geng, and Tingting Dong. "Fingerprint Classification Combining Curvelet Transform and Gray-Level Cooccurrence Matrix." Mathematical Problems in Engineering 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/592928.

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Fingerprint classification is an important indexing scheme to reduce fingerprint matching time for a large database for efficient large-scale identification. The abilities of Curvelet transform capturing directional edges of fingerprint images make the fingerprint suitable to be classified for higher classification accuracy. This paper presents an efficient algorithm for fingerprint classification combining Curvelet transform (CT) and gray-level cooccurrence matrix (GLCM). Firstly, we use fast discrete Curvelet transform warping (FDCT_WARPING) to decompose the original image into five scales Curvelet coefficients and construct the Curvelet filter by Curvelet coefficients relationship at adjacent scales to remove the noise from signals. Secondly, we compute the GLCMs of Curvelet coefficients at the coarsest scale and calculate 16 texture features based on 4 GLCMs. Thirdly, we construct 49 direction features of Curvelet coefficients at the other four scales. Finally, fingerprint classification is accomplished byK-nearest neighbor classifiers. Extensive experiments were performed on 4000 images in the NIST-4 database. The proposed algorithm achieves the classification accuracy of 94.6 percent for the five-class classification problem and 96.8 percent for the four-class classification problem with 1.8 percent rejection, respectively. The experimental results verify that proposed algorithm has higher recognition rate than that of wavelet-based techniques.
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Mukhopadhyay, Anirban, Sourav Kumar, Souvik Roy Chowdhury, et al. "Multi-Lingual Scene Text Detection Using One-Class Classifier." International Journal of Computer Vision and Image Processing 9, no. 2 (2019): 48–65. http://dx.doi.org/10.4018/ijcvip.2019040104.

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The main purpose of scene text recognition is to detect texts in a given image. The problem of text detection and recognition in such images has gained great attention in recent years due to rising demand of several applications like visual based applications, multimedia and content-based retrieval. Due to low accuracies of existing scene text detection methods, an improved pipeline is developed for text localizing task. First, candidate text regions are generated using Maximally Stable Extremal Region and Stroke Width Transform methods that capture true positives along with many false positives. A One Class Classifier is trained to label the candidate regions obtained, as text or non-text, which in this case is suitable as non-text class cannot be adequately represented to train a binary classifier. The one class classifier is trained with some popular feature descriptors like Histogram of Oriented Gradients, Grey Level Co-Occurrence Matrix, Discrete Cosine Transform and Gabor filter. Experimental results show high recall for text containing regions and reducing false positives.
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42

Santhi, K., B. Sowmiya, R. Shalinirajan, V. Vijayashanthi, and V. Vasudhevan. "3-WAY Secured WSN with CSDSM-DNN based Intrusion Detection Model." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 8 (2023): 81–89. http://dx.doi.org/10.17762/ijritcc.v11i8.7926.

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In Wireless Sensor Networks (WSNs), intrusion aims indegrading or even eliminating the capacity of these networks for providing their functions. Thus, in recent years, several ideas are brought and employed. However, these techniques still did not fulfill their requirements in attaining better classification accuracy. This paper proposes a novel Cosine Similarity Distance integrated Sammon Mapping learning layer-Deep Neural Network (CSDSM-DNN)-centricIntrusion Detection Model (IDM) in WSNfor attaining better outcomes. Initially, the nodes are clustered; after that, utilizing Binomial Distribution based Dwarf Mongoose Optimization (BD-DMO), the cluster heads are selected. Then, theIdentity Matrix Function-Kalman Filter (IMF-KF) identified the optimal route. Subsequently, the data is transferred via the secured route. The transferred data is pre-processed and then, the important features are selected. Lastly, to classify whether the data is attacked or non-attacked, the selected features are given into the CSDSM-DNN. Therefore, with the prevailing approaches, the experiential outcomes are evaluated and analogized and it exhibits the proposed model’s higher reliability and efficacy.
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43

Yarlykov, A. D., and O. A. Demin. "Development of a microwave low-pass filter based on a microstrip line projection mode." Russian Technological Journal 13, no. 3 (2025): 92–102. https://doi.org/10.32362/2500-316x-2025-13-3-92-102.

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Objectives. Sections of microstrip lines having finite length are widely used to develop integrated circuits and microwave devices for various purposes, such as power dividers, directional couplers, attenuators, and filters. In particular, low-pass filters in the microwave range are comprised of a cascade connection of regular sections of microstrip lines having various geometric parameters. However, modern approaches to calculating microwave filters using commercial software require large computational and time-consuming resources, especially when carrying out electrodynamic analysis of microstrip lines. The work set out to develop an algorithm and a method for calculating filters using a projection approach to the electrodynamic analysis of microstrip lines that reduces the time required to calculate characteristics of microwave filters while maintaining high accuracy of the obtained results.Methods. The proposed projection approach to the electrodynamic analysis of a microstrip line can be used to rapidly and accurately calculate the main electrodynamic parameters of retardation coefficient and wave impedance across a wide range of changes in the geometrical parameters of the line, as well as its dielectric constant and frequency.Results. Formulas obtained on the basis of analytical expressions for calculating the electrodynamic parameters of a microstrip line are used to describe the nature of changes in the elements of the scattering matrix of multistage low-pass filters in a given frequency band. A developed computer program was used to calculate the values of the elements of the low-pass filter scattering matrix across a wide range of substrate dielectric constant and frequency parameters. The obtained results were compared with the characteristics of filters calculated using commercial software.Conclusions. The proposed approach to calculating the electrodynamic parameters of microstrip lines and consequent elements of the scattering matrix of multistage low-pass filters can significantly reduce the calculation time while achieving a sufficiently high accuracy of the obtained results to significantly reduce labor costs when calculating microwave filters in engineering practice.
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Abdelfatih, Bengana, and Boukli Hacene Ismail. "An Adaptive Image Fusion Algorithm in the NSST Based on CDF 9/7 for Neurodegenerative Diseases." Traitement du Signal 39, no. 4 (2022): 1379–85. http://dx.doi.org/10.18280/ts.390432.

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The neurodegenerative disease such as: Parkinson's disease (PD), mild Alzheimer’s affects many people and has a serious influence on their life, With the quick advancement of computer-aided diagnostic (CAD) methods, early detection is crucial since effective treatment halts the spread of the disease. Image fusion is useful for medical diagnostics. In this paper we propose a multi-modality medical image fusion algorithm in NSST domain. Shearlets (NSST) are decomposed similarly to contourlets (NSCT), except that instead of applying the Laplacian pyramid followed by directional filtering, shearlets use a shear matrix. In this article the Biorthogonal CDF9/7 filter is applied in the shift-invariant shearlet filter banks, then the coefficients of low frequency bands are selected using maximum rule, and using the gradient in each subband high frequency image to motivate the modified pulse coupled neural networks (Modified PCNN). Finally reverse IHS to get the fused color image, all this to optimize the calculation performance and improve the characteristics of the fused image for medical diagnosis. Our approach was validated with several brain diseases modalities: Alzheimer’s…etc. The findings reveal that the suggested image fusion technique has a higher quality than those fused by previous algorithms existing.
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45

Machado, Gabriel, Abdulmohsen Alali, Bryce Hutchinson, Oluwatobi Olorunsola, and Kurt J. Marfurt. "Display and enhancement of volumetric fault images." Interpretation 4, no. 1 (2016): SB51—SB61. http://dx.doi.org/10.1190/int-2015-0104.1.

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Fault picking is a critical, but human-labor-intensive component of seismic interpretation. In a bid to improve fault imaging in seismic data, we have applied a directional Laplacian of a Gaussian operator to sharpen fault features within a coherence volume. We computed an [Formula: see text] matrix of the second moment tensor distance-weighted coherence values that fell within a 3D analysis window about each voxel. The eigenvectors of this matrix defined the orientation of planar discontinuities, whereas the corresponding eigenvalues determined whether these discontinuities were significant. The eigenvectors, which quantified the fault dip magnitude and dip azimuth, defined a natural coordinate system for smoothing of the planar discontinuity. We rotated the data to the new coordinate system and applied the sharpening operator. By comparing the vector dip of the discontinuity to the vector dip of the reflectors, we could apply a filter to either suppress or enhance discontinuities associated with unconformities or low-signal-to-noise-ratio shale-on-shale reflectors. We have revealed the value and robustness of the technique by application to two 3D data volumes from offshore New Zealand, which exhibited polygonal faulting, shale dewatering, and mass transport complexes.
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46

Reddy, G. Ravi Shankar, and Rameshwar Rao. "Instantaneous Frequency Estimation of Multi-Component Non- Stationary Signals using Fourier Bessel series and Time-Varying Auto Regressive Model." International Journal of Electronics and Telecommunications 61, no. 4 (2015): 365–76. http://dx.doi.org/10.2478/eletel-2015-0048.

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Abstract In this paper, we propose a novel technique for Instantaneous Frequency (IF) estimation of multi component non stationary signals using Fourier Bessel Series and Time- Varying Auto Regressive (FB-TVAR) model. In the proposed technique, the Fourier-Bessel (FB) expansion decomposes the multi-component non stationary signal into a number of monocomponent signals and TVAR model is used to model each mono-component signal. In TVAR modeling approach the time varying parameters are expanded as a linear combination of basis functions. In this paper, the TVAR parameters are expanded by a discrete cosine basis functions. The maximum likelihood estimation algorithm for model order selection in TVAR models is also discussed. The Instantaneous Frequency (IF) is extracted from the time-varying parameters by calculating the angles of the estimation error filter polynomial roots. The estimation of the TVAR parameters of a multicomponent signal requires the inversion of a large covariance matrix, while the projected technique (FB-TVAR) requires the inversion of a number of comparatively small covariance matrices with better numerical stability properties. Simulation results are presented for Multi component discrete Amplitude and Frequency modulated (AM-FM) signal
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Song, Seungwoo, Hyun-Woo Kim, Myungjin Cho, and Min-Chul Lee. "Automated Scattering Media Estimation in Peplography Using SVD and DCT." Electronics 14, no. 3 (2025): 545. https://doi.org/10.3390/electronics14030545.

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In this paper, we propose automation of estimating scattering media information in peplography using singular value decomposition (SVD) and discrete cosine transform (DCT). Conventional scattering media-removal methods reduce light scattering in images utilizing a variety of image-processing techniques and machine learning algorithms. However, under conditions of heavy scattering media, they may not clearly visualize the object information. Peplography has been proposed as a solution to this problem. Peplography is capable of visualizing the object information by estimating the scattering media information and detecting the ballistic photons from heavy scattering media. Following that, 3D information can be obtained by integral imaging. However, it is difficult to apply this method to real-world situations since the process of scattering media estimation in peplography is not automated. To overcome this problem, we use automatic scattering media-estimation methods using SVD and DCT. They can estimate the scattering media information automatically by truncating the singular value matrix and Gaussian low-pass filter in the frequency domain. To evaluate our proposed method, we implement the experiment with two different conditions and compare the result image with the conventional method using metrics such as structural similarity (SSIM), feature similarity (FSIMc), gradient magnitude similarity deviation (GMSD), and learned perceptual image path similarity (LPIPS).
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48

Zhou, Xuyang, Long Chen, Changhao Sun, Wei Jia, Naixin Yi, and Wei Sun. "Highly Accurate Attitude Estimation of Unmanned Aerial Vehicle Payloads Using Low-Cost MEMS." Micromachines 16, no. 6 (2025): 632. https://doi.org/10.3390/mi16060632.

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Low-cost MEMS sensors are widely utilized in UAV platforms to address attitude estimation problems due to their compact size, low power consumption, and cost-effectiveness. Diverse UAV payloads pose new challenges for attitude estimation, such as magnetic interference environments and high dynamic environments. In this paper, we propose a hierarchical decoupled attitude estimation algorithm, termed HDAEA. Initially, a novel hierarchical decoupling approach is introduced for the attitude and angle representation of the direction cosine matrix, enabling the representation of angles in a new manner. This method reduces the data dimensionality and nonlinearity of observation equations. Furthermore, a magnetic interference identification algorithm is proposed to compute the magnetic interference intensity accurately and quantitatively. Combining the quantified errors of estimated state variables, an error model for magnetic interference and attitude angles in high-dynamic environments is constructed. Subsequently, the proposed error model is employed to calibrate the hierarchical decoupled angles using accelerometer and magnetometer measurements, effectively mitigating the impact of magnetic interference on the calculation of pitch angles and roll angles. Moreover, the integration of the proposed hierarchical decoupled attitude estimation algorithm with the error-state extended Kalman filter reduces system nonlinearity and minimizes linearization errors. Experimental results demonstrate that HDAEA exhibits significantly improved attitude estimation accuracy of UAV payloads.
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49

Zhao, Xiaobin, Wei Li, Mengmeng Zhang, Ran Tao, and Pengge Ma. "Adaptive Iterated Shrinkage Thresholding-Based Lp-Norm Sparse Representation for Hyperspectral Imagery Target Detection." Remote Sensing 12, no. 23 (2020): 3991. http://dx.doi.org/10.3390/rs12233991.

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In recent years, with the development of compressed sensing theory, sparse representation methods have been concerned by many researchers. Sparse representation can approximate the original image information with less space storage. Sparse representation has been investigated for hyperspectral imagery (HSI) detection, where approximation of testing pixel can be obtained by solving l1-norm minimization. However, l1-norm minimization does not always yield a sufficiently sparse solution when a dictionary is not large enough or atoms present a certain level of coherence. Comparatively, non-convex minimization problems, such as the lp penalties, need much weaker incoherence constraint conditions and may achieve more accurate approximation. Hence, we propose a novel detection algorithm utilizing sparse representation with lp-norm and propose adaptive iterated shrinkage thresholding method (AISTM) for lp-norm non-convex sparse coding. Target detection is implemented by representation of the all pixels employing homogeneous target dictionary (HTD), and the output is generated according to the representation residual. Experimental results for four real hyperspectral datasets show that the detection performance of the proposed method is improved by about 10% to 30% than methods mentioned in the paper, such as matched filter (MF), sparse and low-rank matrix decomposition (SLMD), adaptive cosine estimation (ACE), constrained energy minimization (CEM), one-class support vector machine (OC-SVM), the original sparse representation detector with l1-norm, and combined sparse and collaborative representation (CSCR).
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50

Lee, Jung Keun, and Tae Hyeong Jeon. "Magnetic Condition-Independent 3D Joint Angle Estimation Using Inertial Sensors and Kinematic Constraints." Sensors 19, no. 24 (2019): 5522. http://dx.doi.org/10.3390/s19245522.

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In biomechanics, joint angle estimation using wearable inertial measurement units (IMUs) has been getting great popularity. However, magnetic disturbance issue is considered problematic as the disturbance can seriously degrade the accuracy of the estimated joint angles. This study proposes a magnetic condition-independent three-dimensional (3D) joint angle estimation method based on IMU signals. The proposed method is implemented in a sequential direction cosine matrix-based orientation Kalman filter (KF), which is composed of an attitude estimation KF followed by a heading estimation KF. In the heading estimation KF, an acceleration-level kinematic constraint from a spherical joint replaces the magnetometer signals for the correction procedure. Because the proposed method does not rely on the magnetometer, it is completely magnetic condition-independent and is not affected by the magnetic disturbance. For the averaged root mean squared errors of the three tests performed using a rigid two-link system, the proposed method produced 1.58°, while the conventional method with the magnetic disturbance compensation mechanism produced 5.38°, showing a higher accuracy of the proposed method in the magnetically disturbed conditions. Due to the independence of the proposed method from the magnetic condition, the proposed approach could be reliably applied in various fields that require robust 3D joint angle estimation through IMU signals in an unspecified arbitrary magnetic environment.
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