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Journal articles on the topic 'Hamming window'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Samad, Md Abdus, Jia Uddin, and Md Razu Ahmed. "FIR Filter Design Using Modified Lanczos Window Function." Advanced Materials Research 566 (September 2012): 49–56. http://dx.doi.org/10.4028/www.scientific.net/amr.566.49.

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Attenuated side lobe peak in the range of around ~-45dB is required in many applications of signal processing and measurements. However, the problem is usual window based FIR filter design lies in its side lobes amplitudes that are higher than the requirement of application. We propose a modified Lanczos window function by heuristic by examining the Lanczos window, which has better performance like equiripple, minimum side lobe compared to the several commonly used windows. The proposed window has slightly larger main lobe width of the commonly used Hamming window, while featuring 5.1~18.5 dB smaller side lobe peak. The proposed modified Lanczos window maintains its maximum side lobe peak about -55.2~-51.9 dB compared to -39~-36.7 dB of Hamming window for M=10~14, while offering roughly equal main lobe width. Our simulated results also show significant performance upgrading of the proposed modified Lanczos window compared to the Kaiser, Gaussian, and Lanczos windows. The proposed modified Lanczos window also shows better performance than Dolph-Chebyshev window. Finally, the example of designed low pass FIR filter confirms the efficiency of the proposed modified Lanczos window.

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2

Mottaghi-Kashtiban, M., and M. G. Shayesteh. "New efficient window function, replacement for the Hamming window." IET Signal Processing 5, no. 5 (2011): 499. http://dx.doi.org/10.1049/iet-spr.2010.0272.

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3

Bojkovic, Zoran S., Bojan M. Bakmaz, and Miodrag R. Bakmaz. "Hamming Window to the Digital World." Proceedings of the IEEE 105, no. 6 (June 2017): 1185–90. http://dx.doi.org/10.1109/jproc.2017.2697118.

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4

Ahmad, Ashraf Adamu, Abdullahi Daniyan, and David Ocholi Gabriel. "Selection of window for inter-pulse analysis of simple pulsed radar signal using the short time Fourier transform." International Journal of Engineering & Technology 4, no. 4 (November 17, 2015): 531. http://dx.doi.org/10.14419/ijet.v4i4.5139.

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The electronic intelligence (ELINT) system is used by the military to detect, extract information and classify incoming radar signals. This work utilizes short time Fourier transform (STFT) - time frequency distribution (TFD) for inter-pulse analysis of the radar signal in order to estimate basic radar signal time parameters (pulse width and pulse repetition period). Four well-known windows functions of different and unique characteristics were used for the localization of STFT to determine their various effects on the analysis. The window functions are Hamming, Hanning, Bartlett and Blackman window functions. Monte Carlo simulation is carried out to determine the performance of the signal analysis in presence of additive white Gaussian noise (AWGN). Results show that the lower the transition of main lobe width and higher the peak side lobe, the better the performance of the window function irrespective of time parameter being estimated. This is because 100 percent probability of correct estimation is achieved at signal to noise ratio of about -2dB for Bartlett, 4dB for both Hamming and Hanning, and 9dB for Blackman.

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Lee, Judy P., and Melvin B. Comisarow. "Advantageous Apodization Functions for Magnitude-Mode Fourier Transform Spectroscopy." Applied Spectroscopy 41, no. 1 (January 1987): 93–98. http://dx.doi.org/10.1366/0003702874868016.

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A systematic examination of the efficacy of window functions for reducing the spectral skirt of magnitude-mode Fourier transform spectra is reported. The efficacy is examined for the general case of a damped time-domain signal, with specific cases ranging from undamped to essentially completely damped signals. The choice of the optimal window is dependent upon the required dynamic range and the amount of damping in the time-domain data. For a dynamic range of less than 100:1 and moderate damping, the Hamming window is the window of choice. For larger dynamic ranges or greater damping, the 3-term Blackman-Harris window and the Kaiser-Bessel window are the windows of choice. The 3-term Blackman-Harris window is preferred for a dynamic range of 1,000:1 and the Kaiser-Bessel window is preferred for a dynamic range of 10,000:1. The sensitivity (signal-to-noise ratio) reduction for windows is reported for a damping range from zero to essentially complete damping. All windows examined have the same sensitivity reduction within 25%.

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Wang, Yun Long, and Shi Hu Wang. "An Excellent 2D Window Function." Applied Mechanics and Materials 651-653 (September 2014): 2116–20. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.2116.

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In the aid of sinc sum function and matrix equation a new 2D window function is obtained. It is as simple as a 2D cosine window function. Comparison shows that the new 2D window function can provide much better 2D FIR filters than 2D Hamming window function. Maximum passband ripples are about 2.5-3.5 times smaller and maximum stopband ripples are about 1.5 times smaller with equal or very small different passband and stopband edge frequencies.

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Xu, Shanding, Xiwang Cao, Jiafu Mi, and Chunming Tang. "Simplified Bounds on FHSs Set and Its Strictly Optimal Construction." International Journal of Foundations of Computer Science 31, no. 04 (June 2020): 499–513. http://dx.doi.org/10.1142/s0129054120500215.

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Frequency-hopping sequences (FHSs) with favorite partial Hamming correlation properties are intensively needed in many synchronization and multiple-access systems. Strictly optimal FHS sets are a kind of FHS sets which has optimal Hamming correlation for any correlation window. In this paper, firstly we present simplified representations of the generalized Lempel–Greenberger bound on the partial Hamming autocorrelation of an FHS and the generalized Peng-Fan bound on the partial Hamming correlation of an FHS set, respectively. Secondly, we propose a direct construction of strictly optimal FHS sets, which interprets the previous construction proposed by Cai, Zhou, Yang and Tang. By choosing appropriate parameters and bijections, we present more flexible constructions of strictly optimal FHS sets.

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8

Podder, Prajoy, Tanvir Zaman Khan, Mamdudul Haque Khan, and M. Muktadir Rahman. "Comparative Performance Analysis of Hamming, Hanning and Blackman Window." International Journal of Computer Applications 96, no. 18 (June 18, 2014): 1–7. http://dx.doi.org/10.5120/16891-6927.

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9

AVCİ, Kemal. "Design of fir filters using exponential--Hamming window family." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 24 (2016): 2513–24. http://dx.doi.org/10.3906/elk-1312-246.

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10

Mbachu, C. B. "Height Adjustable Triangular (HAT) Window Function for Impulse Response Modification of Signal Processing Systems." European Journal of Engineering Research and Science 5, no. 3 (March 27, 2020): 358–66. http://dx.doi.org/10.24018/ejers.2020.5.3.1442.

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A widow function, in signal processing and statistics, is a mathematical function that has zero values outside its chosen interval or limit of sequence, normally symmetric around the middle of the interval. Usually the middle of the window is either maximum or near maximum and tappers smoothly as it moves away to the sides. When another function or sequence of data is mathematically multiplied by the window function it forces the product to assume its nature of zero-value outside the interval and tapering from middle to the sides. Windows are finite functions and their main function is to modify an infinite impulse response sequence so as to make it finite within its chosen interval in system design. Several windows are in existence and they include Hamming, rectangular, Han, Kaiser, Triangular, Blackman, Sine, Blackman-Harris, Gaussian, Doph-Chebyshev and Lanczos, windows. Others are Parzen, Nuttall, flat top, Turkey, windows and many more. The window to apply in the design depends on the characteristics of the signal to be processed, types of system to be implemented and quality of output desired. In this paper, a new window called Height Adjustable triangular (HAT) window function is developed and added to the list of windows for signal processing system designs. The effectiveness of the window is tested by examining its characteristics. The adjustment parameter varies the amplitude or height of the window. Result shows that it is stable and linear.

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11

Chew, Kim Mey, Rubita Sudirman, Norhudah Seman, and Ching Yee Yong. "Signal Processing of Microwave Imaging Brain Tumor Detection Using Superposition Windowing." Applied Mechanics and Materials 654 (October 2014): 321–26. http://dx.doi.org/10.4028/www.scientific.net/amm.654.321.

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This paper discusses the selection of window function for signal processing in microwave imaging brain tumor detection. Most of the window functions are non-negative bell-shaped curves. This paper proposed a superposition windowing function for better time series data analyses and enhancement. The performance of the selected five window functions (Hamming, Blackman-Harris, Parzen, Chebyshev and Bartlett-Hanning) and the proposed superposition window were compared and evaluated. The results show the superposition window function is potentially reduce the unwanted noise and preserve important information of the signals.

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12

LIDYAWATI, LITA, PAULINE RAHMIATI, and YULI SUNARTI. "Implementasi Filter Finite Impulse Response (FIR) Window Hamming dan Blackman menggunakan DSK TMS320C6713." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 4, no. 1 (May 2, 2018): 16. http://dx.doi.org/10.26760/elkomika.v4i1.16.

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ABSTRAKFilter didefinisikan sebagai proses atau rangkaian yang melewatkan pita frekuensi tertentu yang diinginkan dan meredam pita frekuensi lainnya. Salah satu metode perancangan filter digital Finite Impulse Response (FIR) adalah metode windowing. Dalam penelitian ini digunakan jenis window Hamming dan Blackman. Simulasi dilakukan dengan menggunakan software Matlab dengan memasukan frekuensi passband, frekuensi stopband, ripple passband, dan stopband attenuation. Dengan frekuensi sampling sebesar 15000 Hz, frekuensi passband sebesar 3000 Hz, frekuensi stopband sebesar 5000 Hz. Setelah simulasi dilakukan implementasi filter dengan parameter yang sama menggunakan DSK TMS 320C6713 dengan bantuan software CCS. Simulasi dan implementasi dilakukan pada semua band frekuensi. Hasil pengujian terhadap implementasi filter adalah respon magnitude, frekuensi cut-off, bandwidth, dan faktor kualitas dengan hasil simulasi tidak menunjukkan perbedaan yang signifikan.Kata kunci: filter digital, windowing, Hamming, Blackman, frekuensi cut-off.ABSTRACTFilter is defined as a process or series that skip certain desired frequency band and other frequency bands drown. One method of designing a digital filter Finite Impulse Response (FIR) is a windowing method. This study used the type of window Hamming and Blackman. Simulations performed using Matlab software by inserting a frequency passband, stopband frequency, passband ripple, and stopband attenuation. With a sampling frequency of 15,000 Hz, a frequency of 3000 Hz passband, stopband frequency of 5000 Hz. After the simulation is completed, implementation of the filter with the same parameters using TMS 320C6713 DSK with the help of software CCS. Simulation and implmentasi performed on all frequency bands. The test results of the implementation of the filter is the Magnitude response, the cut-off frequency, bandwidth, and quality factor with simulation results showed no significant difference.Keywords: digital filter, windowing, Hamming, Blackman, cut-off frequency.

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13

Mbachu, C. B. "Height Adjustable Sine (HAS) Window Function for Impulse Response Modification of Signal Processing Systems." European Journal of Engineering Research and Science 5, no. 3 (March 27, 2020): 367–74. http://dx.doi.org/10.24018/ejers.2020.5.3.1443.

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A widow function, in signal processing and statistics, is a mathematical function that has zero values outside its chosen interval or limit of sequence, normally symmetric around the middle of the interval. Usually the middle of the window is either maximum or near maximum and tappers smoothly as it moves away to the sides. When another function or sequence of data is mathematically multiplied by the window function the product assumes the appearance and characteristics of the window function. That is, the product is also zero-valued outside the interval and tapering from middle to the sides. The impulse response data of some systems used in signal processing truncate suddenly when being designed. Window functions convert the sudden truncation of these impulse response data to gradual truncation. Without this gradual truncation the processing system will degrade the integrity of complex signals when they are applied to them; the degradation appears in form of signal distortions. Windows are used to weight these impulse response data so as to reduce the degradation and distortions. Several windows are in existence and they include Hamming, rectangular, Han, Kaiser, Triangular, Blackman, Sine, Blackman-Harris, Gaussian, Doph-Chebyshev and Lanczos, windows. Others are Parzen, Nuttall, flat top, and Turkey, windows and others. The characteristics of the signal to be processed, types of systems to be implemented and quality of outputs desired determine the best window to weight any particular impulse response data. In this work a new window referred to as Height Adjustable Sine (HAS) window is developed to join the list of the existing windows. The quality of the window is tested by analysing its amplitude, magnitude and phase responses in frequency domain. Result shows that the window is stable and linear.

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14

Al-Barhan, Hussein A., Sinan M. Elyass, Thamir R. Saeed, Ghufran M. Hatem, and Hadi T. Ziboon. "Modified Speech Separation Deep Learning Network Based on Hamming window." IOP Conference Series: Materials Science and Engineering 1076, no. 1 (February 1, 2021): 012059. http://dx.doi.org/10.1088/1757-899x/1076/1/012059.

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15

Bai, Le Qiang, and Xue Wei Zhang. "Improved Window Function in the Application of MFCC Feature Parameter Extraction." Applied Mechanics and Materials 556-562 (May 2014): 3703–6. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3703.

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In view of spectrum leakage and the contradictory problem of spectrum accuracy of main lobe and reducing spectrum leakage, MFCC algorithm based on improved window function is proposed. Improved window function is based on the mathematical analysis of Kaiser window, and under the condition of finite sampling points minuses weighted impact function where is at the frequencies that side lobe peaks of correspond to. The amplitude of improved window compared with Kaiser window is smaller, and main lobe width is the same, solving the conflicting problem of main lobe width and side lobe amplitude and reducing spectrum leakage. The experimental results show that speech recognition rate of MFCC feature parameter extraction algorithm based on improved window function is better than Kaiser window and Hamming window.

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16

Mynuddin, Mohammed. "Designing a Low- Pass Fir Digital Filter by Using Hamming Window and Blackman Window Technique." Science Journal of Circuits, Systems and Signal Processing 4, no. 2 (2015): 9. http://dx.doi.org/10.11648/j.cssp.20150402.11.

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17

Daraghma, Raed S. M. "M-ary phase-shift keying using finite impulse response filter based on window function method." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (February 1, 2021): 451. http://dx.doi.org/10.11591/ijece.v11i1.pp451-457.

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Digital filters are vastly utilized in the area of communication. A perfect digital filter efficiency is significant and hence to design a digital finite impulse response filter (FIR) favorable all the wanted situations is necessary. In this paper, a new proposed FIR digital filter designed, the fineness of the submitted filter is tested in terms of BER and then matched with another window, namely Hamming, Hanning, and Blackman. The design procedure done in the MATLAB software. It is concluded that the Blackman window is the best window to design the FIR digital filter, because it is bit error rate is better than another window.

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18

Tan, Ming, Chunyang Wang, Hui Yuan, Juan Bai, and Lei An. "FDA-MIMO Beampattern Synthesis with Hamming Window Weighted Linear Frequency Increments." International Journal of Aerospace Engineering 2020 (April 16, 2020): 1–8. http://dx.doi.org/10.1155/2020/4851909.

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By utilizing a tiny frequency increment across the array elements, frequency diverse array (FDA) generates a beampattern possessing the property of range-angle-dependent. However, the beampattern of the conventional FDA is “S”-shaped, which means it is coupled in range-angle domains, resulting in low target indication accuracy and poor jamming suppression ability. In this paper, taking advantage of multiple-input multiple-output (MIMO) technique and multiple matched filters, a new FDA framework using Hamming window weighted linear frequency increments is proposed. Correct FDA-MIMO framework and multiple matched filters are used to remove the influence of the time parameter. A range-angle-decoupled beampattern with sharp pencil-shaped mainlobe and low sidelobe levels can be produced. Comparing with the existing FDA-decoupled transmit beampattern design methods, a more focusing beampattern can be achieved. Simulation results validate the superiority of the proposed system.

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Tan, Jingjia, Lesheng He, and Jun Wang. "Signal acquisition and processing system based on zynq dual core." MATEC Web of Conferences 246 (2018): 03001. http://dx.doi.org/10.1051/matecconf/201824603001.

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In order to speed up the acquisition and processing of signal, this paper has developed a signal acquisition and processing system based on zynq platform. Based on the ARM Cortex-A9 dual-core and editable logic unit architecture of Zynq AP SoC platform, this paper implements a fully functional signal acquisition and processing system by software and hardware collaborative design. ARM0 is the main processor that controls system and shared resources. ARM1 is the slave processor. ARM1 is responsible for receiving the data converted by the AD7606 analog-to-digital chip. The data is sent to the Hamming window function IP core created under vivado HLS through the AXI bus. After the data is processed by Hamming window function, it is sent to ARM1 again through AXI bus. OCM acts as the shared memory for ARM0 and ARM1 communication. The Linux system runs on ARM0. The processed data is sent to the upper computer through ethernet through UDP protocol. Utilizing the architecture of the Zynq platform, the system efficiency is improved, and the stability of the system is ensured, so that the FPGA can enter the field of embedded systems.

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Kulagin, V. P., D. A. Akimov, S. A. Pavelyev, and E. O. Guryanova. "Identification of temporal anomalies of spectrograms of vibration measurements of a turbine generator rotor using a recurrent neural network autoencoder." Russian Technological Journal 9, no. 2 (April 26, 2021): 78–87. http://dx.doi.org/10.32362/2500-316x-2021-9-2-78-87.

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A method is proposed for recognizing pre-emergency conditions of rotary installations based on the use of the Hamming window and advanced Deep Learning techniques in retrospective analysis of the results of accounting for the factors of operation of a turbine generator, diagnostics and control under critical impacts. A program of experimental studies on the model of a turbine plant with simulation of faults and receiving vibration signals has been developed. An experiment based on the homostatic method of checking the signal with Hamming windows, in the frequency, time and modulation domains and common initial data, allows one to determine the most promising signal characteristics for identification. A method has been developed for monitoring the state of turbine generators in an automatic mode for timely notification of the CHPP personnel about the appearance of signs of pre-emergency situations, as well as about the nature of faults by the method of predicting the state of a pre-emergency situation using convolutional neural networks implemented in the form of a recurrent autoencoder. Clustering is applied and clusters are identified that correspond to the spectrograms of pre-emergency situations. The effectiveness of the use of the homostatic method in combination with correlation analysis is based on the decision-making model described in more detail in other works.

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Gautam, Ganesh, Surendra Shrestha, and Seongsoo Cho. "Spectral Analysis of Rectangular, Hanning, Hamming and Kaiser Window for Digital Fir Filter." International journal of advanced smart convergence 4, no. 2 (November 30, 2015): 138–44. http://dx.doi.org/10.7236/ijasc.2015.4.2.138.

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Sayed, Inayatullah S., and Siti S. Ismail. "Comparison of Low-Pass Filters for SPECT Imaging." International Journal of Biomedical Imaging 2020 (April 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/9239753.

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In single photon emission computed tomography (SPECT) imaging, the choice of a suitable filter and its parameters for noise reduction purposes is a big challenge. Adverse effects on image quality arise if an improper filter is selected. Filtered back projection (FBP) is the most popular technique for image reconstruction in SPECT. With this technique, different types of reconstruction filters are used, such as the Butterworth and the Hamming. In this study, the effects on the quality of reconstructed images of the Butterworth filter were compared with the ones of the Hamming filter. A Philips ADAC forte gamma camera was used. A low-energy, high-resolution collimator was installed on the gamma camera. SPECT data were acquired by scanning a phantom with an insert composed of hot and cold regions. A Technetium-99m radioactive solution was homogenously mixed into the phantom. Furthermore, a symmetrical energy window (20%) centered at 140 keV was adjusted. Images were reconstructed by the FBP method. Various cutoff frequency values, namely, 0.35, 0.40, 0.45, and 0.50 cycles/cm, were selected for both filters, whereas for the Butterworth filter, the order was set at 7. Images of hot and cold regions were analyzed in terms of detectability, contrast, and signal-to-noise ratio (SNR). The findings of our study indicate that the Butterworth filter was able to expose more hot and cold regions in reconstructed images. In addition, higher contrast values were recorded, as compared to the Hamming filter. However, with the Butterworth filter, the decrease in SNR for both types of regions with the increase in cutoff frequency as compared to the Hamming filter was obtained. Overall, the Butterworth filter under investigation provided superior results than the Hamming filter. Effects of both filters on the quality of hot and cold region images varied with the change in cutoff frequency.

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Federico, Lorenzo, Remco Van Der Hofstad, Frank Den Hollander, and Tim Hulshof. "Expansion of Percolation Critical Points for Hamming Graphs." Combinatorics, Probability and Computing 29, no. 1 (August 5, 2019): 68–100. http://dx.doi.org/10.1017/s0963548319000208.

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AbstractThe Hamming graph H(d, n) is the Cartesian product of d complete graphs on n vertices. Let ${m=d(n-1)}$ be the degree and $V = n^d$ be the number of vertices of H(d, n). Let $p_c^{(d)}$ be the critical point for bond percolation on H(d, n). We show that, for $d \in \mathbb{N}$ fixed and $n \to \infty$, $$p_c^{(d)} = {1 \over m} + {{2{d^2} - 1} \over {2{{(d - 1)}^2}}}{1 \over {{m^2}}} + O({m^{ - 3}}) + O({m^{ - 1}}{V^{ - 1/3}}),$$ which extends the asymptotics found in [10] by one order. The term $O(m^{-1}V^{-1/3})$ is the width of the critical window. For $d=4,5,6$ we have $m^{-3} = O(m^{-1}V^{-1/3})$, and so the above formula represents the full asymptotic expansion of $p_c^{(d)}$. In [16] we show that this formula is a crucial ingredient in the study of critical bond percolation on H(d, n) for $d=2,3,4$. The proof uses a lace expansion for the upper bound and a novel comparison with a branching random walk for the lower bound. The proof of the lower bound also yields a refined asymptotics for the susceptibility of a subcritical Erdös–Rényi random graph.

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Kamışlıoğlu, Bircan, and Nurhan Karaboğa. "Investigation of the performance of the Kaiser-Hamming window in design of QMF bank." Pamukkale University Journal of Engineering Sciences 25, no. 2 (2019): 165–73. http://dx.doi.org/10.5505/pajes.2018.37974.

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Kharsan, Jyoti, Shivani Yadav, and Pranay Kumar Rahi. "Efficient Design of Low Pass FIR Filter by Hamming, Blackman and Rectangular Window Techniques." IJARCCE 6, no. 3 (March 30, 2017): 756–62. http://dx.doi.org/10.17148/ijarcce.2017.63179.

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Chandrosha, Yogesh, Nirmala Maheshwari, and Pranay Kumar Rahi. "Efficient Design of LOE Pass FIR Filter by Hamming, Kaiser and Blackman Window Techniques." IJARCCE 6, no. 3 (March 30, 2017): 896–901. http://dx.doi.org/10.17148/ijarcce.2017.63209.

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Kamışlıoğlu, Bircan, and Nurhan Karaboğa. "Investigation of the performance of the Kaiser-Hamming window in design of QMF bank." Pamukkale University Journal of Engineering Sciences 25, no. 2 (2019): 165–73. http://dx.doi.org/10.5505/pajes.2019.37974.

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Basit, Abdul, Ijaz Mansoor Qureshi, Wasim Khan, Shuja ur Rehman, and Muhammad Mohsin Khan. "Beam Pattern Synthesis for an FDA Radar with Hamming Window-Based Nonuniform Frequency Offset." IEEE Antennas and Wireless Propagation Letters 16 (2017): 2283–86. http://dx.doi.org/10.1109/lawp.2017.2714761.

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Kumar, Sanjay, Kulbir Singh, and Rajiv Saxena. "Analysis of Dirichlet and Generalized “Hamming” window functions in the fractional Fourier transform domains." Signal Processing 91, no. 3 (March 2011): 600–606. http://dx.doi.org/10.1016/j.sigpro.2010.04.011.

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Malik, Jyoti, G. Sainarayanan, and Ratna Dahiya. "Sliding Window Based Fast Corner Matching Palmprint Authentication." International Journal of Computer Vision and Image Processing 1, no. 3 (July 2011): 16–34. http://dx.doi.org/10.4018/ijcvip.2011070102.

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Authentication time is the main and important part of the authentication system. Normally the response time should be fast but as the number of persons in the database increases, there is probability of more response time taken for authentication. The need of fast authentication system arises so that authentication time (matching time) is very less. This paper proposes a sliding window approach to make fast authentication system. The highlight of sliding window method is constant matching time, fast and can match translated images also. Several palmprint matching methods like match by correlation etc. are dependent upon the number of corners detected and so is the matching time. In sliding window method, matching time is constant as the numbers of matching operations are limited and the matching time is independent of the number of corners detected. The palmprint corner features extracted using two approaches Phase Congruency Corner Detector and Harris Corner Detector are binarized so that only useful information (features) is matched. The two approaches of Phase Congruency Corner Detector and Harris Corner Detector, when matched with hamming distance using sliding window can achieve recognition rate of 97.7% and 97.5% respectively.

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Liu, Hong Li, Lei Shao, Hai Bin Zuo, and Nan Liu. "Application of Laser Doppler Technique in Measurement of Explosive Container Based on Frequency Correction." Applied Mechanics and Materials 391 (September 2013): 497–500. http://dx.doi.org/10.4028/www.scientific.net/amm.391.497.

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Dynamic measurement of explosion containment vessel deformation for explosive experiment is obtained using laser doppler effect. The system is based on optical heterodyning technologies, and uses half wave plate, quarter wave plate, polarization beam splitter and acousto-optic modulator to improve the intensity of doppler signal and signal-noise-ratio. Short time fourier transform and energy centrobaric correction method using hamming window is applied to improve the signal processing speed and the accuracy. The experimental results of explosive container are presented under 20g TNT explosion.

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Xie, Hua Long, Fei Li, and Guo Cun Kang. "The Application Research of Six-Axis Force Sensor Used by Trans-Femoral Prosthesis." Advanced Materials Research 683 (April 2013): 741–44. http://dx.doi.org/10.4028/www.scientific.net/amr.683.741.

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Intelligent bionic leg (IBL) is an advanced trans-femoral prosthesis. First, the conception and structure component of IBL are introduced. Then, working principle of six-axis force sensor is analyzed in detail. The type selection and design of filter are discussed. In the end, the data filtering of low pass filter based on hamming window function is established and simulation is done. The simulation indicates that force and torque signal has a significant improvement after filtering and the filter designed in the paper is reasonable.

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Li, Xian Mao, Gao Ming Huang, and Dong Xia. "Spacial Filter of Weighting Method Based on Spectrum Analyse." Advanced Materials Research 605-607 (December 2012): 1890–96. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1890.

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The selection of a certain scope angle signal in the traditional method is to switch the hard switches in antennas, this paper proposes a method, which based on a weighting method to filter the signal in certain directions, namely spacial filter. With array antennas，the compositive signal can be acquired, by which the phrase and plus (weighting) of each unit antenna’s signal be adjusted and then the signals be added. In different time, signals can be selected in any scope of directions through adjusting each channels by different weighting. The weighting parameters can be obtained through the analysis of spacial signal and spacial spectrum, and then obtains an appropriate weighting window function. Simulation shows that Hamming window’s weighting is the best among the three representative windows functions. It can obtain a low sidelobe (-44dB) and less rising edge and declining edges. And the paper also give a hardware structure.

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Eskidere, Ömer, and Ahmet Gürhanlı. "Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features." Computational and Mathematical Methods in Medicine 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/956249.

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The Mel Frequency Cepstral Coefficients (MFCCs) are widely used in order to extract essential information from a voice signal and became a popular feature extractor used in audio processing. However, MFCC features are usually calculated from a single window (taper) characterized by large variance. This study shows investigations on reducing variance for the classification of two different voice qualities (normal voice and disordered voice) using multitaper MFCC features. We also compare their performance by newly proposed windowing techniques and conventional single-taper technique. The results demonstrate that adapted weighted Thomson multitaper method could distinguish between normal voice and disordered voice better than the results done by the conventional single-taper (Hamming window) technique and two newly proposed windowing methods. The multitaper MFCC features may be helpful in identifying voices at risk for a real pathology that has to be proven later.

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Goel, Navdeep, and Kulbir Singh. "Analysis of Dirichlet, Generalized Hamming and Triangular window functions in the linear canonical transform domain." Signal, Image and Video Processing 7, no. 5 (December 10, 2011): 911–23. http://dx.doi.org/10.1007/s11760-011-0280-2.

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Reja, Mohammad Istiaque, Md Golam Murtuza, and Roki Roy. "Combinations of Different FIR Windows for Removal of Baseline and Power Line Noise from Electrocardiogram." Modern Applied Science 12, no. 9 (August 20, 2018): 119. http://dx.doi.org/10.5539/mas.v12n9p119.

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Electrocardiogram (ECG) is a vital tool used for diagnosing various heart diseases. It is the graphical representation of the electrical activity of the heart. But the electrocardiographic signals are often corrupted by noise from diverse sources. The most significant noises that corrupt ECG signal are power line interference and baseline wanders. It is necessary to reduce the amount of these disturbances from ECG signal for proper identification and interpretation of heart condition. This paper investigates the performance of the different 'Band stop filter-High Pass filter' combinations of window based FIR filter for removing the baseline wander and power line noise present in electrocardiogram. The ECG signal is generated and then noises are added to the ECG signal using MATLAB® where filters are designed and analyzed using Filter Design and Analysis Tool (FDATool). 49 different 'Band stop filter-High Pass filter' combinations are made using seven different FIR windows namely Bartlett, Chebyshev, Hamming, Hann, Kaiser, Rectangular, Triangular. For filter order of 350 and 450, the performance of different window combinations are compared and analyzed in terms of Signal power, Peak-to-peak value, Signal to Noise Ratio (SNR) and Mean Square Error (MSE) of the filtered output. A further analysis of the waveforms of the filtered output show that the combinations where both the bandstop and highpass filters are either Kaiser or Rectangular window i.e. Kaiser-Kaiser, Kaiser-Rectangular, Rectangular-Kaiser and Rectangular-Rectangular windows give the best performance in reducing both the baseline noise and high frequency power line noise. It is also found that the reduction of baseline noise is better if 450 filter order is used instead of 350 order in the above mentioned best four combinations, although the amount of delay for 450 order is slightly higher.

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Cao, Cai Feng, Hua Rong Liang, and Guo Chao Liang. "Research on Information Technology with Voiceprint Authentication Algorithm and its Implementation on Mobile Terminal." Advanced Materials Research 886 (January 2014): 698–701. http://dx.doi.org/10.4028/www.scientific.net/amr.886.698.

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Mobile internet and its application is hot information technology. The study integrates and improves some speech processing algorithms to make them suitable for the mobile terminal environment and to realize user identity authentication. It uses one body's unique voiceprint information which has the characteristics of convenient, concise, efficient and safe. By studying pre-emphasis, hamming window and other speech signal pretreatment, the voiceprint feature extraction technique of Mel cepstrum parameters, pattern matching algorithm DTW, a algorithm scheme is established. The scheme has been implemented and verified. It is suitable for treating small amount of words voice authentication.

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Serreqi, Alessio, and Melvin B. Comisarow. "Frequency Interpolation of Discrete, Apodized, Magnitude Lineshapes." Applied Spectroscopy 41, no. 2 (February 1987): 288–95. http://dx.doi.org/10.1366/000370287774986985.

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All Fourier spectrometers have a residual error in frequency measurement arising from the discrete nature of the experimental Fourier spectrum. This residual error is a systematic error which has a maximum value of half the channel spacing in the discrete spectrum. This systematic error can be reduced by interpolation of values on the discrete lineshape. The residual error remaining after interpolation has not yet been determined for apodized Fourier spectra. In this work, a systematic study of frequency interpolation of discrete, apodized, magnitude-mode lineshapes is reported. Absolute maximum frequency errors as a percentage of the discrete channel spacing are reported in graphical and tabular form as a function of the type of apodization window, the type of function used for three-point frequency interpolation, the number of zero-fillings, and ( T/ r), the ratio of the acquisition time to the relaxation time of the time domain signal. The results allow independent choice of the window function most appropriate for the dynamic range of the spectrum and the interpolating function/zero-filling level which optimizes the accuracy of frequency measurement. General observations are (1) that the interpolation error is reduced by an order of magnitude for each additional level of zero-filling and (2) that the interpolation error is essentially independent of T/r. For the Hanning window, the Hamming window, the three-term Blackman-Harris window, and the Kaiser-Bessel window, the parabola is the interpolating function of choice.

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Jin, Zhaoyang, Ling Xia, Minming Zhang, and Yiping P. Du. "Background-Suppressed MR Venography of the Brain Using Magnitude Data: A High-Pass Filtering Approach." Computational and Mathematical Methods in Medicine 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/812785.

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Conventional susceptibility-weighted imaging (SWI) uses both phase and magnitude data for the enhancement of venous vasculature and, thus, is subject to signal loss in regions with severe field inhomogeneity and in the peripheral regions of the brain in the minimum-intensity projection. The purpose of this study is to enhance the visibility of the venous vasculature and reduce the artifacts in the venography by suppressing the background signal in postprocessing. A high-pass filter with an inverted Hamming window or an inverted Fermi window was applied to the Fourier domain of the magnitude images to enhance the visibility of the venous vasculature in the brain after data acquisition. The high-pass filtering approach has the advantages of enhancing the visibility of small veins, diminishing the off-resonance artifact, reducing signal loss in the peripheral regions of the brain in projection, and nearly completely suppressing the background signal. The proposed postprocessing technique is effective for the visualization of small venous vasculature using the magnitude data alone.

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Sahu, Durgesh, Mukesh Chandra, and Pranay Kumar Rahi. "Magnitude and Phase Response of High Pass FIR filter using Rectangular, Hamming and Bartlett Window Techniques." IJARCCE 6, no. 3 (March 30, 2017): 773–77. http://dx.doi.org/10.17148/ijarcce.2017.63182.

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Mohan Reddy, N. Jagan. "Comparison Study of Hamming and Kaiser Window over Band Pass Filter Banks in Cochlear Implant System." International Journal of Electronics and Communication Engineering 6, no. 5 (May 25, 2019): 35–44. http://dx.doi.org/10.14445/23488549/ijece-v6i5p106.

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Xu, Qing Kun, Zhi Qiang Du, and Jun He. "The Design of the Intelligent Voice Recognition System Based on Labview." Applied Mechanics and Materials 734 (February 2015): 383–86. http://dx.doi.org/10.4028/www.scientific.net/amm.734.383.

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The recognition of speech sounds test system based on virtual instrument was designed successfully. For years, virtual instrument has become a huge active communication platform for user, and covered the multiple industries and fields of applications, becoming the data acquisition and instrument control the best choice. Based on the Labview 8.5 software platform, combined with PC sound card, microphones and other hardware acquisition of speech signal, the speech signal is filtered. Through the Hamming window, and power spectrum, the recognition of speech signal is realized. After the actual test and application, software operation is stable and reliable, with certain practicability and value of popularization and application.

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Hashmi, Anas. "Perceptual Evaluation of Speech Quality for Inexpensive Recording Equipment." Acoustics 3, no. 1 (March 10, 2021): 200–211. http://dx.doi.org/10.3390/acoustics3010014.

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This research studies the perceptual evaluation of speech signals using an inexpensive recording device. Different types of noise-reduction and electronic enhancement filters viz. Hamming window, high-pass filter (HPF), Wiener-filter and no-speech activity-cancelling were applied in compliance with the testing conditions such as P.835. In total, 41 volunteers participated in the study for identifying the effects of those filters following a repeatable approach. Performance was assessed in terms of advanced perceptual audio features. This study is believed to be beneficial for both users and device manufacturers as the suggested technique is relatively simple to embed in operational device algorithms or in the master GPU.

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Siegel, Nisan, Joseph Rosen, and Gary Brooker. "Faithful reconstruction of digital holograms captured by FINCH using a Hamming window function in the Fresnel propagation." Optics Letters 38, no. 19 (September 30, 2013): 3922. http://dx.doi.org/10.1364/ol.38.003922.

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Anantha, Alifia Putri, Bambang Hidayat, and Nur Andini. "STEGANALISIS SINYAL WICARA BERFORMAT .WAV MENGGUNAKAN KOMBINASI METODE MEL-FREQUENCY CEPSTRAL COEFFICIENT (MFCC) DAN LINEAR DISCRIMINANT ANALYSIS (LDA)." TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika 3, no. 1 (August 22, 2019): 9. http://dx.doi.org/10.25124/tektrika.v3i1.2205.

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Dalam penelitian ini, telah dirancang sebuah sistem yang dapat melakukan steganalisis suatu berkas sinyal wicara berformat .wav, dengan menganalisis karakteristik ciri suatu file speech. Metode yang digunakan untuk mengekstraksi ciri sinyal wicara adalah Mel-Frequency Cepstral Coefficient (MFCC), sedangkan untuk menyeleksi ciri digunakan metode Linear Discriminant Analysis (LDA) metode yang digunakan untuk menyeleksi ciri adalah Linear Discriminant Analysis (LDA). Hasil keluaran dari sistem ini berupa kondisi yang menyatakan berkas sinyal wicara merupakan berkas sinyal wicara asli, tersisip pesan tersembunyi, atau tersisip noise. Support Vector Machine (SVM) digunakan untuk pengklasifikasian dan performansi sistem terbaik yang didapatkan adalah 82,86%. Kondisi tersebut diraih oleh penggunaan hamming window, overlapping, panjang frame 30 ms, dan mel-filter bank yang dibangun berjumlah 20 mel-filter bank.

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Yohanes, Banu W. "Linear Prediction and Long Term Predictor Analysis and Synthesis." Techné : Jurnal Ilmiah Elektroteknika 16, no. 01 (April 3, 2017): 49–58. http://dx.doi.org/10.31358/techne.v16i01.158.

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Spectral analysis may not provide an accurate description of speech articulation. This article presents an experimental setup of representing speech waveform directly in terms of timevarying parameters. It is related to the transfer function of the vocal tract. Linear Prediction, Long Term Predictor Analysis, and Synthesis filters are designed and implemented, as well as the theory behind introduced. The workflows of the filters are explained by detailed and codes of those filters. Original waveform files are framed with Hamming window and for each frames the filters are applied, and the reconstructed speeches are compared to original waveforms. The results come out that LP and LTP analysis can be used in DSPs due to its periodical characteristic, but some distortion might be coursed, which examined in the experiments.

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Srinivasan, R., Tessy Thomas, and Bopanna Lakshmi. "Power Spectral Density Computation and Dominant Frequencies Identification from the Vibration Sensor Output under Random Vibration Environment." Defence Science Journal 70, no. 6 (October 12, 2020): 692–700. http://dx.doi.org/10.14429/dsj.70.15535.

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The objective of the modal and spectral analysis is to determine the vibration characteristics of structures such as natural frequencies, dominant frequencies and mode shapes. Such modal and spectral analyses have major relevance to the study of the dynamic properties of the structures undergoing dynamic vibration. Methods for the estimation of the power spectral density and identification of the dominant frequencies from the sensor responses under random vibrating environment are presented in this paper. Periodogram using FFT, Welch Method and MUSIC algorithm are used to analyse the known frequency sinusoids with additive white noise and output of the vibration sensor mounted on the test object. The resultant spectra obtained using the methods and their corresponding errors with the reference spectrum are analysed. The Welch method is further studied with three different windows, namely, Hann, Hamming and Blackman-Harris and with three different overlapping criteria viz. 0%, 25% and 50%. The same algorithm and methodology were adopted and compared in two different platforms: Mathematical Model Simulation and Hardware-In-Loop-Simulation. It is observed from the results that Welch Method with 25% overlap used in combination either with Hann or Blackman-Harris window yields more accurate results, compared to other combinations. Also, 25% overlap provides better execution time trade-off compared to 50% overlap.

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Boonyasiriwat, Chaiwoot, Paul Valasek, Partha Routh, Weiping Cao, Gerard T. Schuster, and Brian Macy. "An efficient multiscale method for time-domain waveform tomography." GEOPHYSICS 74, no. 6 (November 2009): WCC59—WCC68. http://dx.doi.org/10.1190/1.3151869.

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This efficient multiscale method for time-domain waveform tomography incorporates filters that are more efficient than Hamming-window filters. A strategy for choosing optimal frequency bands is proposed to achieve computational efficiency in the time domain. A staggered-grid, explicit finite-difference method with fourth-order accuracy in space and second-order accuracy in time is used for forward modeling and the adjoint calculation. The adjoint method is utilized in inverting for an efficient computation of the gradient directions. In the multiscale approach, multifrequency data and multiple grid sizes are used to overcome somewhat the severe local minima problem of waveform tomography. The method is applied successfully to 1D and 2D heterogeneous models; it can accurately recover low- and high-wavenumber components of the velocity models. The inversion result for the 2D model demonstrates that the multiscale method is computationally efficient and converges faster than a conventional, single-scale method.

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Tozzi, Alberto Eugenio, Francesco Gesualdo, Emanuele Urbani, Alessandro Sbenaglia, Roberto Ascione, Nicola Procopio, Ileana Croci, and Caterina Rizzo. "Digital Surveillance Through an Online Decision Support Tool for COVID-19 Over One Year of the Pandemic in Italy: Observational Study." Journal of Medical Internet Research 23, no. 8 (August 13, 2021): e29556. http://dx.doi.org/10.2196/29556.

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Background Italy has experienced severe consequences (ie, hospitalizations and deaths) during the COVID-19 pandemic. Online decision support systems (DSS) and self-triage applications have been used in several settings to supplement health authority recommendations to prevent and manage COVID-19. A digital Italian health tech startup, Paginemediche, developed a noncommercial, online DSS with a chat user interface to assist individuals in Italy manage their potential exposure to COVID-19 and interpret their symptoms since early in the pandemic. Objective This study aimed to compare the trend in online DSS sessions with that of COVID-19 cases reported by the national health surveillance system in Italy, from February 2020 to March 2021. Methods We compared the number of sessions by users with a COVID-19–positive contact and users with COVID-19–compatible symptoms with the number of cases reported by the national surveillance system. To calculate the distance between the time series, we used the dynamic time warping algorithm. We applied Symbolic Aggregate approXimation (SAX) encoding to the time series in 1-week periods. We calculated the Hamming distance between the SAX strings. We shifted time series of online DSS sessions 1 week ahead. We measured the improvement in Hamming distance to verify the hypothesis that online DSS sessions anticipate the trends in cases reported to the official surveillance system. Results We analyzed 75,557 sessions in the online DSS; 65,207 were sessions by symptomatic users, while 19,062 were by contacts of individuals with COVID-19. The highest number of online DSS sessions was recorded early in the pandemic. Second and third peaks were observed in October 2020 and March 2021, respectively, preceding the surge in notified COVID-19 cases by approximately 1 week. The distance between sessions by users with COVID-19 contacts and reported cases calculated by dynamic time warping was 61.23; the distance between sessions by symptomatic users was 93.72. The time series of users with a COVID-19 contact was more consistent with the trend in confirmed cases. With the 1-week shift, the Hamming distance between the time series of sessions by users with a COVID-19 contact and reported cases improved from 0.49 to 0.46. We repeated the analysis, restricting the time window to between July 2020 and December 2020. The corresponding Hamming distance was 0.16 before and improved to 0.08 after the time shift. Conclusions Temporal trends in the number of online COVID-19 DSS sessions may precede the trend in reported COVID-19 cases through traditional surveillance. The trends in sessions by users with a contact with COVID-19 may better predict reported cases of COVID-19 than sessions by symptomatic users. Data from online DSS may represent a useful supplement to traditional surveillance and support the identification of early warning signals in the COVID-19 pandemic.

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Jeyarani, A. D., Reena Daphne, and Chettiyar Vani Vivekanand. "IMPROVED PSO BASED DRIVER’S DROWSINESS DETECTION USING FUZZY CLASSIFIER." JOURNAL OF ADVANCES IN CHEMISTRY 13, no. 9 (February 22, 2017): 6489–502. http://dx.doi.org/10.24297/jac.v13i9.5804.

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In this drowsiness detection framework two actions including brain and visual features are utilised to distinguish the various levels of drowsiness. These actions are provided by the EEG and EOG signal brain actions. From the EEG and EOG signals the peculiarities like mean, peak, pitch, maximum, minimum, standard deviation are assessed . In these peculiarities we decide on some best attributes - peak and pitch employing an IPSO strategy that picks up the best threshold esteem. These signals are then offered into the STFT which is employed to discover the signal length, producing a STFT network from the intermittent hamming window,the output of which are energy signals alpha and beta. These energy signals are offered into the MCT to get an alpha mean and a beta mean -the most chosen and outstanding attributes. These are then subjected to fuzzy based classification to give a precise result checking over the maximum values in the alpha and the beta series .

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