Abstract
The work proposes a new algorithm for the estimation of the ICA model, an algorithm based on secant method and successive approximations. The first sections briefly present the standard FastICA algorithm based on the Newton method and a new version of the FastICA algorithm. The proposed algorithm to estimate the independent components combines the secant iterations with successive approximations technique. The final section presents the results of a comparative analysis experimentally derived conclusions concerning the performance of the proposed method. The tests were performed of several samples of signal files.
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Constantin, D., State, L. (2008). A Version of the FastICA Algorithm Based on the Secant Method Combined with Simple Iterations Method. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2008. Lecture Notes in Computer Science, vol 5099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69905-7_36
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DOI: https://doi.org/10.1007/978-3-540-69905-7_36
Publisher Name: Springer, Berlin, Heidelberg
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