Fractional synchrosqueezing transform for enhanced multicomponent signal separation by Yangyang Li, Dzati Athiar Ramli

“…This paper introduces a multicomponent signal separation method based on innovative Fractional Synchrosqueezing Transform (FrSST). …”
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Clutter Mitigation in Echocardiography Using Sparse Signal Separation by Javier S. Turek, Michael Elad, Irad Yavneh

“…In this paper, we apply a method called Morphological Component Analysis (MCA) for sparse signal separation with the objective of reducing such clutter artifacts. …”
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On a Real-Time Blind Signal Separation Noise Reduction System by Ka Fai Cedric Yiu, Siow Yong Low

“…Blind signal separation has been studied extensively in order to tackle the cocktail party problem. …”
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Blind signal separation algorithm based on temporal predictability and differential search algorithm by Lei CHEN, Li-yi ZHANG, Yan-ju GUO, Yong HUANG, Jing-yi LIANG

Subjects: “…blind signal separation…”
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Blind speech signals separation based on Borel measure peaks for under-determined mixtures by GUO Wen-qiang1, QIU Tian-shuang1, ZHA Dai-feng1

“…The statistical characteristics of stable distribution was briefly introduced,and a new method for identifying the independent components of an Alpha-stable random vector for under-determined mixtures was proposed.The method was based on an estimate of the discrete spectral measure for the characteristic function of an Alpha-stable random vector.Simulations demonstrate that the proposed method can identify independent components and the basis vectors of mixing matrix in the so-called under-determined case of more sources than mixtures,and obtained the good effect in the speech signals separation application.…”
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Overview of research progress on blind separation methods for single channel communication signal by Wen DENG, Zhitao HUANG, Xiang WANG

Subjects: “…blind signal separation…”
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Passive UHF tag collision resolution on PHY layer by Hai-feng WU, Yu ZENG

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User signal recovery based on channel matrix division by GUO Bin, BAI Xue-mei, F.Mohammed

Subjects: “…blind signal separation…”
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Nonlinear Blind Source Separation Algorithm Using Glowworm Swarm Optimization with Baffle Effect by Pubo Huang, Yu Wei

“…Their validity is confirmed by effect of the signal separation test.…”
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Nonlinear blind source separation algorithm based on spline interpolation and artificial bee colony optimization by Lei CHEN, Shi-zhong GAN, Li-yi ZHANG, Guang-yan WANG

“…A post-nonlinear blind source separation algorithm based on spline interpolation fitting and artificial bee colony optimization was proposed for the more complicated nonlinear mixture situations.The separation model was constructed by using the spline interpolation to fit the inverse nonlinear distortion function and using entropy as the separation criterion.The spline interpolation node parameters were solved by the modified artificial bee colony optimization algorithm.The correlation constraint was added into the objective function for limiting the solution space and the outliers wuld be restricted in the separation process.The results of speech sounds separation experiment show that the proposed algorithm can effectively realize the signal separation for the nonlinear mixture.Compared with the traditional separation algorithm based on odd polynomial fitting,the proposed algorithm has higher separation accuracy.…”
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Blind separation algorithm of PCMA signals with different symbol rates based on DG-PSP by Yi-ming GUO, Hua PENG, Yong YANG, Xue-juan WEI, Hao WANG

“…A blind separation algorithm was proposed for PCMA signals with different symbol rates based on double grid per-survivor processing (DG-PSP).The channel states and two input signal components were treated as two dynamic grids,receiving mixed-signal reconstructed by respectively iterative updating the two groups of grid status,thus achieving blind signal separation.The joint iterative decoding separation structure was focused,and a detailed analysis and comparison under different error estimation of parameters was shown.The complexity of the algorithm is similar to the traditional PSP algorithm.Simulation results show that,a gain of about 2 dB in signal-noise ratio can be obtained after the first iteration at a bit error rate of 10⁻²,and a gain of nearly 3 dB in signal-noise ratio can be obtained after the second iteration.…”
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Algorithm of underdetermined convolutive blind source separation for high reverberation environment by Yuan XIE, Tao1 ZOU, Weijun SUN, Shengli XIE

“…To separate the underdetermined convolutive mixture signals in the high reverberation environment, a novel algorithm of underdetermined convolutive blind source separation was proposed.Aiming at the influence of high reverberation environment, a global impulse response network was designed to weaken reverberation echo, improving signal quality.A new mathematical model of time-frequency mixing signals was established based on the global impulse response network.The global impulse response matrix which shortened the length of the traditional impulse response, reduced the approximation error of model transformation caused by high reverberation.The real-time update learning rules of model parameters were designed based on the theory of nonnegative matrix factorization, and the source signal separation problem was converted into the model parameter optimization problem, achieving blind source separation of mixing signals.Experimental results show that the proposed algorithm can effectively realize the blind source separation of Chinese and English speech and music signals, and the comparision with existing popular algorithms verified the superiority of the proposed algorithm.…”
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Noncontact Multiperson Respiratory Detection Method Based on Blind Source Separation by Xuan YANG, Ziying WANG, Li ZHANG, Heng ZHAO, Hong HONG

“…In addition, this article proposes a multiperson respiratory signal separation algorithm based on noncircular complex independent component analysis and analyzes the impact of different respiratory signal parameters on the separation effect. …”
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Deep Learning-Based Channel Estimation to Mitigate Channel Aging in Massive MIMO With Pilot Contamination by Hiroki Hirose, Siyuan Yang, Tomoaki Ohtsuki, Mondher Bouazizi

“…In time division duplex (TDD)-based massive multiple-input multiple-output (MIMO) systems, accurate channel state information (CSI) between the base station (BS) and user terminal (UT) is crucial for efficient signal processing, including received signal separation and transmission precoding. However, due to the time-varying nature of wireless channels and the limited coherence time, the pilot signals must be short, and the number of orthogonal pilot sequences is finite. …”
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A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments by Guoyi Zhang, Hongxiang Zhang, Zhihua Shen, Deren Kong, Chenhao Ning, Fei Shang, Xiaohu Zhang

“…In this study, we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression. We introduce a mixture Gaussian model constrained under a joint spatial-temporal-transform domain Dirichlet process, combined with total variation regularization to achieve disturbance signal suppression. …”
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METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA by HUANG GangJing, FAN YuGang, HUANG GuoYong

“…First,analyze the CEEMD vibration signals,decompose them into intrinsic mode function（ IMF） components signal of different scales; then through the sensitivity evaluation algorithm,decompose and recombine the signals,and use Fast ICA to reduce their noise; in the end,conduct Hilbert envelope spectrum analysis to the signals separated by the Fast ICA,to obtain the fault feature information. …”
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Blind decoding method for a multi-cell massive antenna array system by Binbin YAN, Lei SHEN, Xianyang JIANG, Yu HAN

“…In order to overcome the pilot contamination and reduction of decoding performance resulted by neighbouring cell pilot sequences reuse in multi-cell massive array MIMO system，a blind decoding method based on ICA was proposed.The proposed blind decoding method used ICA to separate the received signals of multi-cell users without using pilot sequences.Thus，pilot contamination was avoided and decoding performance would be optimized.Every user’s angle-of-arrival（AOA）was estimated for recognizing the desired user signals and overcoming the uncertainty of signals separated by ICA.The analytical performance and numerical results show that the proposed method has a better performance compared to MMSE decoding and blind decoding method based on singular value decomposition（SVD）.…”
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FEATURE EXTRACTION METHOD OF SOUND SIGNAL TO ROLLING BEARING BASED ON BLIND SOURCE SEPARATION AND MORLET WAVELET by LI JingJiao, CHEN EnLi, LIU YongQiang

“…Firstly,the wavelet packet is used to change the single channel of the voice signal separated into two virtual channels,then using BSS to extract the source of signal. …”
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Heart abnormality classification using ECG and PCG recordings with novel PJM-DJRNN by Nadikatla Chandrasekhar, Sujatha Canavoy Narahari, Sreedhar Kollem, Samineni Peddakrishna, Archana Penchala, Babji Prasad Chapa

“…The proposed method involves noise removal from ECG and PCG signals separately using the Brownian Functional-based BesseL Filter (BrF-BLF) and Frequency Ratio-based Butterworth Filter (FR-BWF), decomposition of the signals using Hamming-based Ensemble Empirical Mode Decomposition (HEEMD), and clustering of the signals as normal and abnormal using Root Farthest First Clustering (RFFC). …”
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