Abstract
This paper proposes a novel Independent Component Analysis algorithm based on the use of genetic algorithms intended for its application to the field of non-linear speech processing. Independent Component Analysis (ICA) is a method for finding underlying factors from multidimensional statistical data, so it can be efficiently applied to suppress interferences and demodulate information in MultiInput-MuliOutput (MIMO) systems. © Springer-Verlag Berlin Heidelberg 2003.
Cite
CITATION STYLE
Rojas, F., Puntonet, C. G., Rojas, I., & Ortega, J. (2003). An independent component analysis evolution based method for nonlinear speech processing. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2687, 679–686. https://doi.org/10.1007/3-540-44869-1_86
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