Blind Signal Separation Algorithm with Independent Component Analysis (ICA) by Means of Neural Training: Design and Development with Newer Approaches
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Abstract
Independent Component Analysis (ICA) and its mathematical ideas are presented for the problem of Blind Signal Separation (BSS) and multichannel blind deconvolution of independent source signals. BSS and ICA are emerging techniques that aspire to recover unobserved signals or sources from the observed mixtures. The aims of this paper are to review some new approaches and implement some new and unique idea regarding the problem of blind signal separation with ICA. Computer based simulations illustrate the performances of the developed algorithms.
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Keywords- Blind source separation; Independent component analysis; Neural network; Learning algorithm.
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