Abstract
The independent component analysis (ICA) problem originates from many practical areas, but there has not been any mathematical theory to solve it completely. In this paper, we establish a mathematical theory to solve it under the condition that the number of super-Gaussian sources is known. According to this theory, a step by step optimization algorithm is proposed and demonstrated well on solving the ICA problem with both the super- and sub-Gaussian sources.
This work was supported by the Natural Science Foundation of China for Projects 60471054 and 40035010.
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Gao, D., Ma, J., Cheng, Q. (2005). A Step by Step Optimization Approach to Independent Component Analysis. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_153
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DOI: https://doi.org/10.1007/11427391_153
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
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