Local Convergence Analysis of FastICA and Related Algorithms

Abstract

The FastICA algorithm is one of the most prominent methods to solve the problem of linear independent component analysis (ICA). Although there have been several attempts to prove local convergence properties of FastICA, rigorous analysis is still missing in the community. The major difficulty of analysis is because of the well-known sign-flipping phenomenon… (More)
DOI: 10.1109/TNN.2007.915117

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Cite this paper

@article{Shen2008LocalCA, title={Local Convergence Analysis of FastICA and Related Algorithms}, author={Hao Shen and Martin Kleinsteuber and Knut H{\"u}per}, journal={IEEE Transactions on Neural Networks}, year={2008}, volume={19}, pages={1022-1032} }