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Local Convergence Analysis of FastICA and Related Algorithms

Date

Authors

Shen, Hao

Kleinsteuber, M

Hueper, Knut

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

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

Keywords

Keywords: Approximate Newton method; Convergence analysis; FastICA; FastICA algorithms; Gram-Schmidt; Higher orders; Local convergences; Orthonormalization; Parallelized versions; Polar decompositions; Principal fiber bundle; Qr decompositions; Rigorous analysis; S Approximate Newton method; Convergence analysis; FastICA; Independent component analysis (ICA); Principal fiber bundle

URI

http://hdl.handle.net/1885/33157

Collections

Open Access Research

Source

IEEE Transactions on Neural Networks

Type

Journal article

DOI

10.1109/TNN.2007.915117

Restricted until

2037-12-31

Downloads

File

Description

01_Shen_Local_Convergence_Analysis_of_2008.pdf (503.76 KB)