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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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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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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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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