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 Multilnput-MuliOutput (MIMO) systems.
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Rojas, F., Puntonet, C.G., Rojas, I., Ortega, J. (2003). An Independent Component Analysis Evolution Based Method for Nonlinear Speech Processing. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_86
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DOI: https://doi.org/10.1007/3-540-44869-1_86
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