Research Article
Mixed Audio Signal Separation Using Independent Component Analysis
Folorunso O
Corresponding Author : Folorunso O,
Electrical/Electronic Department, University of Benin, Nigeria.
Email ID : oladipofolorunso@yahoo.com
Received : 2014-09-11 Accepted : 2014-10-07 Published : 2014-10-08
Abstract : Blind Source Separation (BSS) is a statistical approach to separating individual signals from an observed mixture of a group of signals, which relies on little assumptions of the signals and the mixing processes or media. This paper covers the general overview of Independent Component Analysis (ICA), an algorithm for achieving BSS techniques with application to real life activities. The ICA algorithm developed using MATLAB 2012, was used to separate mixture of audio signals recorded and it proved effective.
Keywords : Blind Source Signals, Independent analysis.
Citation : Folorunso O. (2014). Mixed Audio Signal Separation Using Independent Component Analysis. J. of Computation in Biosciences and Engineering. V2I1 DOI : 10.5281/zenodo.893557
Copyright : © 2014 Folorunso O. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Journal of Computation in Biosciences and Engineering
ISSN : 2348-7321
Volume 2 / Issue 1
ScienceQ Publishing Group

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