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Journal articles on the topic 'Mixed signal processing'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Qi, Yang, Taichu Shi, and Ben Wu. "Wideband Mixed Signal Separation Based on Photonic Signal Processing." Telecom 2, no. 4 (2021): 413–29. http://dx.doi.org/10.3390/telecom2040024.

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The growing needs for high-speed and secure communications create an increasing challenge to the contemporary framework of signal processing. The coexistence of multiple high-speed wireless communication systems generates wideband interference. To protect the security and especially the privacy of users’ communications requires stealth communication that hides and recovers private information against eavesdropping attacks. The major problem in interference management and stealth information recovery is to separate the signal of interest from wideband interference/noise. However, the increasing

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Zou, JinFeng, Yi-an Cui, and Jing Xie. "Self-potential signal processing based on NMF." Journal of Physics: Conference Series 2895, no. 1 (2024): 012023. https://doi.org/10.1088/1742-6596/2895/1/012023.

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Abstract In recent years, new algorithms have been continuously applied in the field of geophysical data processing, all of which have achieved good results. However, there is currently no dedicated signal separation method for self-potential field signal processing. In this paper, we propose a self-potential signal separation algorithm based on non-negative matrix factorization (NMF) to perform blind source signal separation. We aim to separate different self-potential signals from the collected mixed signals, laying the foundation for subsequent work such as feature recognition. We utilized

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3

Vogel, Ch, St Mendel, P. Singerl, and F. Dielacher. "Digital signal processing for data converters in mixed-signal systems." e & i Elektrotechnik und Informationstechnik 126, no. 11 (2009): 390–95. http://dx.doi.org/10.1007/s00502-009-0689-2.

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Celik, Husamettin, and Nurhan Karaboga. "Blind Source Separation with Multi-Objective Optimization for Denoising." Elektronika ir Elektrotechnika 28, no. 5 (2022): 62–67. http://dx.doi.org/10.5755/j02.eie.31232.

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Blind Source Separation is an optimization method frequently used in statistical signal processing applications. There are many application areas such as ambient listening, denoising, signal detection, and so on. In this study, a new Strength Pareto Evolutionary Algorithm 2-based signal separation method is proposed, which combines Multi-Objective Optimization and Blind Source Separation algorithms. The proposed method has been tested for denoising, which is widely used in biomedical signal processing. That is, the Electrocardiogram (ECG) and White Gaussian Noise are mixed together with normal

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Zhao, Xiaoming, Qiang Tuo, Ruosi Guo, and Tengteng Kong. "Research on Music Signal Processing Based on a Blind Source Separation Algorithm." Annals of Emerging Technologies in Computing 6, no. 4 (2022): 24–30. http://dx.doi.org/10.33166/aetic.2022.04.003.

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The isolation of mixed music signals is beneficial to the extraction and identification of music signal features and to enhance music signal quality. This paper briefly introduced the mathematical model for separating blind source from mixed music signals and the traditional Independent Component Analysis (ICA) algorithm. The separation algorithm was optimized by the complex neural network. The traditional and optimized ICA algorithms were simulated in MATLAB software. It was found that the time-domain waveform of the signal isolated by the improved ICA-based separation algorithm was closer to

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Shumway, R. H., E. Smart, and D. A. Clauter. "Mixed Signal Processing for Regional and Teleseismic Arrays." Bulletin of the Seismological Society of America 98, no. 1 (2008): 36–51. http://dx.doi.org/10.1785/0120060140.

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Li, Yanping, Linyan Wu, Tao Wang, Nuo Gao, and Qi Wang. "EEG Signal Processing Based on Genetic Algorithm for Extracting Mixed Features." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 06 (2019): 1958008. http://dx.doi.org/10.1142/s0218001419580084.

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In order to improve the classification of motor imagery EEG accuracy, this paper proposes a method based on Genetic Algorithm (GA) EEG signal classification method to extract mixed characteristics. This method uses wavelet analysis and Hilbert–Huang Transform (HHT) to analyze EEG signals and optimizes the characteristics through Common Spatial Patterns (CSP). Finally, the 14 sub features are optimized by GA, and the weights and data credibility of different sub features are obtained. The experiment was tested with 2003BCI competition data and the EEG signal collected by the laboratory. The acc

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Deng, Jun, Hua Yong Tan, Lun Cai Liu, and Lin Tao Liu. "Research of a Mixed-Signal Programmable SoC Based on FPAA." Applied Mechanics and Materials 556-562 (May 2014): 1741–44. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.1741.

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This paper presents a novel architecture for mixed-signal SoC, which integrates a Field Programmable Analog Array (FPAA) into a SoC based on 32-bit RISC CPU. The FPAA unit can be configured as Filter, Comparator, Gain Amplifier, and so on. The proposed mixed-signal SoC can transform the intermediate frequency (IF) analog signal to baseband digital signal and realize the real-time baseband signal processing, besides this, which can transmit the modulated IF signals which are converted from baseband signals by digital up-conversion (DUC). The proposed mixed-signal SoC is a transceiver on chip ac

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Song, Ning, Lian Ying Ji, and Yong Peng Xu. "Denoising of the Respiratory Signal of Electrical Bio-Impedance." Advanced Materials Research 718-720 (July 2013): 1024–28. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.1024.

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Human respiratory signal provides important information in modern medical care. In daily life, respiratory signal is usually captured under different motion states with the help of Electrical impedance pneumography (EIP). Consequently, the captured signal is easily corrupted by electronic/electromagnetic noise, internal mechanical vibration of the lung and motion artifacts. Because respiratory signal and interferences co-exist in an overlapping spectra manner, classical filtering method cannot work here. In this paper, we present a new signal processing method for eliminating the noise and int

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10

Jin, Xiang Yang, and Shi Sheng Zhong. "Research on Identification Method of Multi-Mixed Vibration Signal of Aeroengine." Key Engineering Materials 419-420 (October 2009): 801–4. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.801.

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The effectiveness of separation and identification of mechanical signals vibrations is crucial to successful fault diagnosis in the condition monitoring and diagnosis of complex machines.Aeroengine vibration signals always include many complicated components, blind source separation (BSS) provides a efficient way to separate the independent component.In order to get the most effective algorithm of vibration signal separation,experiment has been done to acquire plenty of multi-mixed rotor vibration signals,three sets of vibration data generated from aeroengine rotating shafts were separated fro

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11

Hao, Yongmei, Ni Qin, Zhixiang Xing, Yujia Wu, and Yunfei Yue. "Research on Gas Pipeline Multi-Point Leak Signal Processing and Source Locating Using VMD, BSS and Relative Entropy." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 10 (2019): 1959033. http://dx.doi.org/10.1142/s021800141959033x.

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The early multi-point leakage source signals of urban gas pipeline are weak and can be easily affected by environmental noise and signal interference between adjacent sources, which causes large leakage positioning error. In this paper, an integrated signal processing method combining VMD, BSS and Relative entropy for multi-point pipeline leakage signal and source positioning is presented. Firstly, VMD and Relative entropy were employed to obtain effective IMF mode components and their features during the decomposition for pipeline leakage signal. Relative entropy was used to improve signal-to

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12

Zhang, Long, Guo Ying Zeng, Deng Feng Zhao, and Hong Qiang Zeng. "Application of VC++ and MATLAB Mixed-Programming Based on MATCOM in Signal Processing." Applied Mechanics and Materials 201-202 (October 2012): 61–64. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.61.

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By research of the mix technology of VC++ and Matlab based on Matcom software, the insufficiencies of data processing in VC++ and visual programming in Matlab have been sloved effectively in signal processing. The own definition functions by matlab can be converted to the C code with Matcom,then the functions can be called anywhere if you need.Using this mix technology, the vibration signals collected by UA307 data acquisition card have been transformed by FFT and the results are consistent with Matlab’s. The mixed-program can operate independently without Matlab software and this method is a

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13

Shah, Gautam A., and Tejmal S. Rathore. "Current Trends in the Mixed-Mode Signal Processing Architectures." IETE Journal of Education 48, no. 3-4 (2007): 115–20. http://dx.doi.org/10.1080/09747338.2007.11657876.

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14

Zhao, Wen Li, Yuan Ping Yin, and Jin Liu. "Medium-Low-Frequency Signal Detection and Simulation Based on the Principle of Stochastic Resonance." Applied Mechanics and Materials 105-107 (September 2011): 1991–94. http://dx.doi.org/10.4028/www.scientific.net/amm.105-107.1991.

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The principle of stochastic resonance in bistable system is introduced firstly. The medium-low-frequency periodic signal and multi-frequency harmonic signal (the large parameter signal) are common in mechanical failure, but it is difficult to achieve stochastic resonance in these signals detection. The signal modulation characteristic is used in this paper to transform the various frequency components into small parameter signals which satisfy the adiabatic approximation theory. On the basis of that, weak signal detection based on stochastic resonance theory is realized. Then a mixing circuit

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15

Mirhassani, M., M. Ahmadi, and G. A. Jullien. "Low-Power Mixed-Signal CVNS-Based 64-Bit Adder for Media Signal Processing." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 16, no. 9 (2008): 1141–50. http://dx.doi.org/10.1109/tvlsi.2008.2000731.

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16

Ryndin, Konoplev, Lysenko, Kulikova, and Popov. "Highly Sensitive Signal Processing Devices for Capacitive Transducers of Micromechanical Accelerometers." Electronics 8, no. 9 (2019): 932. http://dx.doi.org/10.3390/electronics8090932.

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In this paper, the principles of the open-loop frequency-based signal processing devices for capacitive MEMS accelerometers are used to develop three CMOS IP-core (Intellectual Property core) projects of highly sensitive signal processing devices with frequency output. Signal processing devices designed in accordance with the considered method form an output of rectangular pulses whose frequencies equal a difference of signal frequencies from two identical generators with micromechanical accelerometer capacitive transducers in their frequency control circuits. First, the analog project scheme

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17

Wu, Ben, Yang Qi, Chenxi Qiu, and Ying Tang. "Wideband Anti-Jamming Based on Free Space Optical Communication and Photonic Signal Processing." Sensors 21, no. 4 (2021): 1136. http://dx.doi.org/10.3390/s21041136.

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We propose and demonstrate an anti-jamming system to defend against wideband jamming attack. Free space optical communication is deployed to provide a reference for jamming cancellation. The mixed signal is processed and separated with photonic signal processing method to achieve large bandwidth. As an analog signal processing method, the cancellation system introduces zero latency. The radio frequency signals are modulated on optical carriers to achieve wideband and unanimous frequency response. With wideband and zero latency, the system meets the key requirements of high speed and real-time

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18

Xu, Pengfei, Yinjie Jia, and Mingxin Jiang. "Blind audio source separation based on a new system model and the Savitzky-Golay filter." Journal of Electrical Engineering 72, no. 3 (2021): 208–12. http://dx.doi.org/10.2478/jee-2021-0029.

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Abstract Blind source separation (BSS) is a research hotspot in the field of signal processing. This scheme is widely applied to separate a group of source signals from a given set of observations or mixed signals. In the present study, the Savitzky-Golay filter is applied to smooth the mixed signals, adopt a simplified cost function based on the signal to noise ratio (SNR) and obtain the demixing matrix accordingly. To this end, the generalized eigenvalue problem is solved without conventional iterative methods. It is founded that the proposed algorithm has a simple structure and can be easil

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19

Gebara, Edward, and Christian Carlowitz. "Technical Committee (TC)-15 RF/Mixed Mixed-Signal Integrated Circuits and Signal Processing Committee Report [MTT Society News]." IEEE Microwave Magazine 23, no. 12 (2022): 99–100. http://dx.doi.org/10.1109/mmm.2022.3203951.

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20

Zhang, Shenghuan, and Ye Cheng. "Masking and noise reduction processing of music signals in reverberant music." Journal of Intelligent Systems 31, no. 1 (2022): 420–27. http://dx.doi.org/10.1515/jisys-2022-0024.

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Abstract Noise will be inevitably mixed with music signals in the recording process. To improve the quality of music signals, it is necessary to reduce noise as much as possible. This article briefly introduces noise, the masking effect, and the spectral subtraction method for reducing noise in reverberant music. The spectral subtraction method was improved by the human ear masking effect to enhance its noise reduction performance. Simulation experiments were carried out on the traditional and improved spectral subtraction methods. The results showed that the improved spectral subtraction meth

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21

Martinez-Ramos, Cynthia, Citlalli Gaona-Tiburcio, Francisco Estupiñan-López, et al. "Smart Corrosion Monitoring in AA2055 Using Hidden Markov Models and Electrochemical Noise Signal Processing." Materials 18, no. 12 (2025): 2865. https://doi.org/10.3390/ma18122865.

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This work explores the application of Hidden Markov Models (HMMs) for the classification and reconstruction of corrosion mechanisms in the aerospace-grade aluminum alloy AA2055 from the signals obtained by electrochemical noise (EN) analysis. Using the PELT algorithm to segment the signal based on relevant changepoints, distinct corrosion states within the segments are isolated and identified, including general, localized, and mixed corrosion based on statistical signal features, which are used to create the probabilistic structure of HMMs through the initiation, transition, and emission matri

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22

Tsividis, Y. "Mixed-Domain Systems and Signal Processing Based on Input Decomposition." IEEE Transactions on Circuits and Systems I: Regular Papers 53, no. 10 (2006): 2145–56. http://dx.doi.org/10.1109/tcsi.2006.882822.

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23

Robinson, William H., and D. Scott Wills. "Efficiency Analysis for a Mixed-Signal Focal Plane Processing Architecture." Journal of VLSI signal processing systems for signal, image and video technology 41, no. 1 (2005): 65–80. http://dx.doi.org/10.1007/s11265-005-6251-5.

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24

Yuan, Fei. "CMOS time-to-digital converters for mixed-mode signal processing." Journal of Engineering 2014, no. 4 (2014): 140–54. http://dx.doi.org/10.1049/joe.2014.0044.

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25

Yang, Xu, Chen Zhuang, Wenquan Feng, et al. "A Fast Acquisition Algorithm for Hybrid Signals of 5G and BeiDou B1." Applied Sciences 13, no. 13 (2023): 7818. http://dx.doi.org/10.3390/app13137818.

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With the large-scale use of BeiDou navigation and 5G technology worldwide, integrating BeiDou navigation and communication has become a hot research topic in navigation and positioning technology. Low-cost, miniaturized, and susceptible mixed-signal receivers will become the future receiver technology development trend. However, the current receiver technology still faces the challenge of further improving the positioning service capability and communication quality, which includes the lack of practical analysis of the compatibility between signals and the lack of mixed-signal processing capab

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26

Shen, Weiguo, Wei Wang, Jiawei Zhu, Huaji Zhou, and Shunling Wang. "Pruning- and Quantization-Based Compression Algorithm for Number of Mixed Signals Identification Network." Electronics 12, no. 7 (2023): 1694. http://dx.doi.org/10.3390/electronics12071694.

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Source number estimation plays an important role in successful blind signal separation. At present, the application of machine learning allows the processing of signals without the time-consuming and complex work of manual feature extraction. However, the convolutional neural network (CNN) for processing complex signals has some problems, such as incomplete feature extraction and high resource consumption. In this paper, a lightweight source number estimation network (LSNEN), which can achieve a robust estimation of the number of mixed complex signals at low SNR (signal-to-noise ratio), is stu

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Yultrisna, Yultrisna, and Andi Syofyan. "SINUSOIDAL NOISE CANCELATION DENGAN MENGGUNAKAN DIGITAL SIGNAL PROCESSING STARTER KIT TMS320C6713." Elektron : Jurnal Ilmiah 4, no. 2 (2012): 67–74. http://dx.doi.org/10.30630/eji.4.2.33.

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Original speech signal is needed both in telecommunications and in some instruments in a variety of fields. Not infrequently, the original audio signal is damaged due to noise. This noise can cause the original signal changes in the actual form. In the final project will be designed FIR filter to remove noise by using TMS320C6713 DSK. Sound signal to be input to the mixed noise removal filter system noise. The mixed voice signal will be searched by subtracting the signal difference to noise signal output FIR filter to get the signal e (n), and then do an adaptation resulting filter coefficient

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Tai-Cheng Lee and Chin-Chi Chen. "A mixed-signal GFSK demodulator for Bluetooth." IEEE Transactions on Circuits and Systems II: Express Briefs 53, no. 3 (2006): 197–201. http://dx.doi.org/10.1109/tcsii.2005.858320.

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Panovic, M., and A. Demosthenous. "Motion estimation processor using mixed-signal approach." IEEE Transactions on Circuits and Systems II: Express Briefs 53, no. 6 (2006): 492–96. http://dx.doi.org/10.1109/tcsii.2006.873830.

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30

Wang, Liyuan, Huafeng He, Zhen Li, Buma Xiao, and Tao Zhou. "Mainlobe Jamming Suppression via Joint Polarization-Range-Doppler Processing." Remote Sensing 17, no. 12 (2025): 1995. https://doi.org/10.3390/rs17121995.

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In the field of electromagnetic countermeasures, suppressing mainlobe jamming represents a critical challenge requiring urgent resolution. Conventional polarization-based anti-jamming techniques, which fundamentally rely on obtaining pure jamming signals for prior parameter estimation, demonstrate limited effectiveness against co-frequency mainlobe suppression jamming. To tackle this problem, this paper proposes an innovative joint polarization-range-Doppler processing framework for airborne dual-polarized radar systems. Initially, we develop a polarized eigen-element surrogate technique to ac

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Asghar, Malik Summair, Saad Arslan, and HyungWon Kim. "Analog Convolutional Operator Circuit for Low-Power Mixed-Signal CNN Processing Chip." Sensors 23, no. 23 (2023): 9612. http://dx.doi.org/10.3390/s23239612.

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In this paper, we propose a compact and low-power mixed-signal approach to implementing convolutional operators that are often responsible for most of the chip area and power consumption of Convolutional Neural Network (CNN) processing chips. The convolutional operators consist of several multiply-and-accumulate (MAC) units. MAC units are the primary components that process convolutional layers and fully connected layers of CNN models. Analog implementation of MAC units opens a new paradigm for realizing low-power CNN processing chips, benefiting from less power and area consumption. The propo

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Park, Shinwoong, and Sanjay Raman. "Analysis and Optimization of Multisection Capacitive DACs for Mixed-Signal Processing." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 27, no. 3 (2019): 679–90. http://dx.doi.org/10.1109/tvlsi.2018.2888593.

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Ma, Yongqiang, Badong Chen, Pengju Ren, Nanning Zheng, Giacomo Indiveri, and Elisa Donati. "EMG-Based Gestures Classification Using a Mixed-Signal Neuromorphic Processing System." IEEE Journal on Emerging and Selected Topics in Circuits and Systems 10, no. 4 (2020): 578–87. http://dx.doi.org/10.1109/jetcas.2020.3037951.

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Shi, Lan, Christopher Soell, Benjamin Pfundt, et al. "A flexible mixed-signal image processing pipeline using 3D chip stacks." Journal of Real-Time Image Processing 14, no. 3 (2016): 517–34. http://dx.doi.org/10.1007/s11554-016-0628-5.

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35

Fang, Lixiong, Jianwen Zhang, Yi Ran, et al. "Blind Signal Separation with Deep Residual Networks for Robust Synthetic Aperture Radar Signal Processing in Interference Electromagnetic Environments." Electronics 14, no. 10 (2025): 1950. https://doi.org/10.3390/electronics14101950.

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With the rapid development of electronic technology, the electromagnetic interference encountered by airborne synthetic aperture radar (SAR) is no longer satisfied with a single type of interference, and it often encounters both suppressive and deceptive interference. In this manuscript, an algorithm based on blind signal separation (BSS) and deep residual learning is proposed for airborne SAR multi-electromagnetic interference suppression. Firstly, theoretical airborne SAR imaging in a multi-electromagnetic interference environment model is established, and the signal-mixed model of multi-ele

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Zhan, Xin Wu, and Wu Jiao Dai. "Dam Deformation Analysis Based on Independent Component Analysis." Applied Mechanics and Materials 212-213 (October 2012): 859–62. http://dx.doi.org/10.4028/www.scientific.net/amm.212-213.859.

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Independent component analysis (ICA) is a recent and well-known technique used to separate mixtures of signals. It can separate independent components from mixed signals and has many advantages in blind signal separation, redundancy removal and processing of frequency aliasing problems. Deformation monitoring data can be regarded as the digital signals series which is composed of different frequency. After making test on ICA in processing dam observation data we can draw a conclusion that it is practical and applicative for ICA to evaluate the stability of the dam and reflect the working condi

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Li, Dengao, Junmin Zhao, Hongyan Liu, and Defeng Hao. "The Application of FastICA Combined with Related Function in Blind Signal Separation." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/953745.

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Blind source separation (BSS) has applications in the fields of data compression, feature recognition, speech, audio, and biosignal processing. Identification of ECG signal is one of the challenges in the biosignal processing. Proposed in this paper is a new method, which is the combination of related function relevance to estimated signal and negative entropy in fast independent component analysis (FastICA) as objective function, and the iterative formula is derived without any assumptions; then the independent components are found by maximizing the objective function. The improved algorithm

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Taillefer, Chris, and Gordon W. Roberts. "TIME-INTERLEAVED MIXED-SIGNAL TEST CORE DIGITIZERS." SYNCHROINFO JOURNAL 7, no. 3 (2021): 27–30. http://dx.doi.org/10.36724/2664-066x-2021-7-3-27-30.

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System-on-Chip (SoC) is one of the main driving forces that have been re-shaping the consumer electronics industry. The SoC alternative to conventional systems design is growing in popularity as the device packing densi escalates due to the evolution of semiconductor technology. Moreover, the decrease in semiconductor feature size is permitting the increase of clock frequencies and component operating speed. These advancements necessitate the integration of system components due to package parasitics and lengthy interconnect. Furthermore, SoC devices offer a cheaper and more compact solution t

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Taillefer, Chris, and Gordon W. Roberts. "TIME-INTERLEAVED MIXED-SIGNAL TEST CORE DIGITIZERS." SYNCHROINFO JOURNAL 7, no. 3 (2021): 27–30. http://dx.doi.org/10.36724/2664-066x-2021-7-3-27-30.

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System-on-Chip (SoC) is one of the main driving forces that have been re-shaping the consumer electronics industry. The SoC alternative to conventional systems design is growing in popularity as the device packing densi escalates due to the evolution of semiconductor technology. Moreover, the decrease in semiconductor feature size is permitting the increase of clock frequencies and component operating speed. These advancements necessitate the integration of system components due to package parasitics and lengthy interconnect. Furthermore, SoC devices offer a cheaper and more compact solution t

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40

Liu, Shiwei, Yanhua Sun, Lingsong He, and Yihua Kang. "Weak Signal Processing Methods Based on Improved HHT and Filtering Techniques for Steel Wire Rope." Applied Sciences 12, no. 14 (2022): 6969. http://dx.doi.org/10.3390/app12146969.

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As one of the most important processes in steel wire rope inspection, defect signal processing is of great significance in guaranteeing safety and precision measurement. Aiming at the weak signal detection of steel wire rope with mixed strands and noise, a combined signal processing method based on magnetic flux leakage testing and multi-step filtering techniques are proposed in this paper. The experiments are first introduced and performed on three typical types of steel wire rope with diameters of 28 mm, 32 mm, 45 mm, and different wire broken defects detected under liftoff distances of 13 m

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Stankovic, Srboljub, Bratislav Iricanin, Dragana Nikolic, et al. "MSV signal processing system for neutron-gamma discrimination in a mixed field." Nuclear Technology and Radiation Protection 27, no. 2 (2012): 165–70. http://dx.doi.org/10.2298/ntrp1202165s.

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Based on the principles derived from Campbell?s theorem, this paper carries out an analysis of the possibilities of Campbell?s mean square value signal processing system. The mean square value mode is especially suitable for measurements performed in a mixed radiation field, because the quantities of electrical charge involved in the interactions of the two types of radiation are substantially different. The measuring detector element may be an adequate ionization chamber and/or semiconductor components for mixed n-? fields. An examination of the discrimination of gamma in relation to the neut

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Kavitha, MV S.Ranjitha Dr Suresh H. N. "REVIEW PAPER ON EFFICIENT VLSI AND FAST FOURIER TRANSFORM ARCHITECTURES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 3 (2017): 15–20. https://doi.org/10.5281/zenodo.345685.

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A fast Fourier transform (FFT) is any fast algorithm for computing the DFT. The development of FFT algorithms had a tremendous impact on computational aspects of signal processing and applied science. The decimation-in-time (DIT) fast Fourier transform (FFT) very often has advantage over the decimation-in-frequency (DIF) FFT for most real-valued applications, like speech/image/video processing, biomedical signal processing, and time-series analysis, etc., since it does not require any output reordering. Fast Fourier Transform (FFT) has the major role in obtaining the signal characteristics wit

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43

Cao, Huiliang, Rang Cui, Wei Liu, et al. "Dual mass MEMS gyroscope temperature drift compensation based on TFPF-MEA-BP algorithm." Sensor Review 41, no. 2 (2021): 162–75. http://dx.doi.org/10.1108/sr-09-2020-0205.

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Purpose To reduce the influence of temperature on MEMS gyroscope, this paper aims to propose a temperature drift compensation method based on variational modal decomposition (VMD), time-frequency peak filter (TFPF), mind evolutionary algorithm (MEA) and BP neural network. Design/methodology/approach First, VMD decomposes gyro’s temperature drift sequence to obtain multiple intrinsic mode functions (IMF) with different center frequencies and then Sample entropy calculates, according to the complexity of the signals, they are divided into three categories, namely, noise signals, mixed signals an

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Lv, Miao Rong, Jian Lu, and Zhi Qiang Chen. "BOU-Based Cycle Determination for Different Kinds of Mechanical Vibration Signals." Applied Mechanics and Materials 220-223 (November 2012): 2217–23. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2217.

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The cycle of each vibration component of a mixed signal is a very important parameter for reciprocating mechanical vibration signal processing. The cycle determination also has an important influence to obtain the typical characteristics of every sub-signal, to achieve the fault detection and diagnosis of the equipment. But signals acquired at the scene tend to a mixture of a variety of vibration components that have their own periodic characteristics. This paper mainly proposes a method based on the conception of the basic operation unit(BOU) for mechanical vibration signal processing, and th

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Jastrzebska-Perfect, Patricia, George D. Spyropoulos, Claudia Cea, et al. "Mixed-conducting particulate composites for soft electronics." Science Advances 6, no. 17 (2020): eaaz6767. http://dx.doi.org/10.1126/sciadv.aaz6767.

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Bioelectronic devices should optimally merge a soft, biocompatible tissue interface with capacity for local, advanced signal processing. Here, we introduce an organic mixed-conducting particulate composite material (MCP) that can form functional electronic components by varying particle size and density. We created MCP-based high-performance anisotropic films, independently addressable transistors, resistors, and diodes that are pattern free, scalable, and biocompatible. MCP enabled facile and effective electronic bonding between soft and rigid electronics, permitting recording of neurophysiol

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Saleh, B., and N. Subotic. "Time-variant filtering of signals in the mixed time frequency domain." IEEE Transactions on Acoustics, Speech, and Signal Processing 33, no. 6 (1985): 1479–85. http://dx.doi.org/10.1109/tassp.1985.1164753.

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Jameel, Jaleel Sadoon. "Medical Image Denoising Using Mixed Transforms." Journal of University of Babylon for Engineering Sciences 26, no. 4 (2018): 272–81. http://dx.doi.org/10.29196/jub.v26i4.804.

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In this paper, a mixed transform method is proposed based on a combination of wavelet transform (WT) and multiwavelet transform (MWT) in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI) or Computed Tomography (CT) images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results sho

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Sadler, Brian M. "Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics." Journal of Research of the National Institute of Standards and Technology 119 (September 2014): 529. http://dx.doi.org/10.6028/jres.119.020.

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Miyashita, Daisuke, Ryo Yamaki, Kazunori Hashiyoshi, et al. "An LDPC Decoder With Time-Domain Analog and Digital Mixed-Signal Processing." IEEE Journal of Solid-State Circuits 49, no. 1 (2014): 73–83. http://dx.doi.org/10.1109/jssc.2013.2284363.

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Lee, Jinsu, Dongjoo Shin, Youchang Kim, and Hoi-Jun Yoo. "A 17.5-fJ/bit Energy-Efficient Analog SRAM for Mixed-Signal Processing." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 25, no. 10 (2017): 2714–23. http://dx.doi.org/10.1109/tvlsi.2017.2664069.

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