Abstract
The local stability analysis of maximum nongaussianity estimation (MNE) is investigated for nonquadratic functions in independent component analysis (ICA). Using trigonometric function, we first derive the local stability condition of MNE for nonquadratic functions without any approximation as has been made in previous literatures. The research shows that the condition is essentially the generalization of Xu's one-bit-matching ICA theorem in MNE. Secondly, based on the generalized Gaussian model (GGM), the availability of local stability condition and robustness to outliers are addressed for three typical nonquadratic functions for various distributed independent components. © Springer-Verlag Berlin Heidelberg 2006.
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CITATION STYLE
Wang, G., Xu, X., & Hu, D. (2006). Local stability analysis of maximum nongaussianity estimation in independent component analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3971 LNCS, pp. 1133–1139). Springer Verlag. https://doi.org/10.1007/11759966_167
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