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Blind Signal Separation, An Overview
2001Blind Signal Separation (BSS) is the process of recovering independent signals that correspond to the individual source signals using only observed linear mixtures of these. In an acoustic context, these source signals are correlated in time and are assumed to be independent of each other.
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Blind Separation of Acoustic Signals
2001This chapter presents an overview of criteria and algorithms for the blind separation of linearly mixed acoustic signals. Particular attention is paid to the underlying statistical formulations of various approaches to the convolutive blind signal separation task, and comparisons to other blind inverse problems are made.
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Simultaneous Graph Learning and Blind Separation of Graph Signal Sources
IEEE Signal Processing Letters, 2021Mohammad B Shamsollahi +2 more
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Blind separation of signal sources
2008Blind source separation (BSS) is a field developed in signal processing and neural network communities over last 15-20 years. It found numerous applications in science and engineering such as acoustics, biomedical signal analysis, communications, image segmentation and deconvolution, spectroscopy, bioinformatics, chemometrics, etc.
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A Quadratic Programming Approach to Blind Equalization and Signal Separation
IEEE Transactions on Signal Processing, 2009Zhi Ding, Jamal Tuqan, J Tuqan
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Blind source separation based on time-frequency signal representations
IEEE Transactions on Signal Processing, 1998Adel Belouchrani, M G Amin
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Blind signal separation for speech signals with noise
2014 IEEE International Conference on Mechatronics and Automation, 2014Shuping Lv, Cheng Zhang
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