The aim of the present paper is to propose a estimation algorithm of the ICA model, an algorithm based on successive approximations. The convergence rate of the successive approximations method are substantiated for the bidimensional case, a case which presents interest from a practical point of view, and we want to establish the performances of the proposed algorithm to estimate the independent components. Comparative analysis is done and experimentally derived conclusions on the performance of the proposed method are drawn in the last section of the paper for signals recognition applications. © 2008 Springer-Verlag.
CITATION STYLE
Constantin, D., & State, L. (2008). An improved algorithm for estimating the ICA model concerning the convergence rate. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5098 LNCS, pp. 400–408). Springer Verlag. https://doi.org/10.1007/978-3-540-70517-8_39
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