An Efficient Algorithm by Kurtosis Maximization in Reference-Based Framework

This paper deals with the optimization of kurtosis for complex-valued signals in the independent component analysis (ICA) framework, where source signals are linearly and instantaneously mixed. Inspired by the recently proposed reference-based contrast schemes, a similar contrast function is put forward, based on which a new fast fixed-point (FastICA) algorithm is proposed. The new optimization method is similar in spirit to the former classical kurtosis-based FastICA algorithm but differs in the fact that it is much more efficient than the latter in terms of computational speed, which is significantly striking with large number of samples. The performance of this new algorithm is confirmed through computer simulations.

Keywords

Blind source separation, independent component analysis, kurtosis, reference-based contrast functions, fastICA, complex-valued signals

Citation

Radioengineering. 2015 vol. 24, č. 2, s. 544-551. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2015/15_02_0544_0551.pdf

Document type

Peer-reviewed

Document version

Published version

Language of document

en

Document licence

Creative Commons Attribution 3.0 Unported License
http://creativecommons.org/licenses/by/3.0/