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Blind source separation (BSS) problem is an open area of research that requires further investigations. Various algorithms were presented in the literature based on second-order statistics and higher-order statistics. The computational complexity of those methods is a challenging task and must be carefully considered to produce fast BSS algorithms. In blind source extraction (BSE) using linear predictors,...
This paper presents a method of blind source separation (BSS) of autoregressive (AR) signals for complete and over-complete cases. It is based on a new separation matrix estimated from the null space (NS) of the mixture. Analysis of a mixture equation is carried out to find out the analytical representation of the separating matrix used for estimating the input source signals. The Eigenvectors of...
This paper presents an efficient architecture of a fixed-point Fast Independent Component analysis (FastICA) in field programmable gate array (FPGA). The algorithm separates up to four signals using four sensors. A prestage QR decomposition is used to improve the speed of eigenvalues and eigenvectors evaluation of the covariance matrix. Moreover, a symmetric orthogonalization of the unit estimation...
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