J.M. Górriz, J.C. Méndez, C.G. Puntonet, M. Salmerón, and M.J. Cazalla (Spain)
Independent Component Analysis, Genetic Algorithms,FastICA, MatLab
This paper presents a design for a tool for the blind separa tion of signals (BSS) using the Matlab visual environment, together with a new method for signal separation that incor porates both independent component analysis (ICA) and genetic algorithms (GAs). ICA has been proposed to re solve the problem of BSS, while GAs comprise an efficient artificial intelligence technique for the optimization of di verse problems. The algorithm proposed combines these two approaches, its efficiency being essential for applica tions presenting both a high degree of dimensionality and time restrictions (i.e. real time applications such as occur in biomedicine and in finance).
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