Document Type

Article

Publication/Presentation Date

2-18-2006

Abstract/Description

The fast fixed-point independent component analysis (ICA) algorithm has been widely used in various applications because of its fast convergence and superior performance. However, in a highly dynamic environment, real-time adaptation is necessary to track the variations of the mixing matrix. In this scenario, the gradient-based online learning algorithm performs better, but its convergence is slow, and depends on a proper choice of convergence factor. This paper develops a gradient-based optimum block adaptive ICA algorithm (OBA/ICA) that combines the advantages of the two algorithms. Simulation results for telecommunication applications indicate that the resulting performance is superior under time-varying conditions, which is particularly useful in mobile communications.

Publication Title

EURASIP Journal on Applied Signal Processing

Required Publisher’s Statement

All SpringerOpen publications are open access: Every article appearing in any SpringerOpen journal and any book published with SpringerOpen is 'open access', meaning that:The article/book is universally and freely accessible via the Internet, in an easily readable format. All publications are deposited immediately upon publication, without embargo, in an agreed format - current preference is XML with a declared DTD - in at least one widely and internationally recognized open access repository. The author(s) or copyright owner(s) irrevocably grant(s) to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate the article/book in its entirety or in part, in any format or medium, provided that no substantive errors are introduced in the process, proper attribution of authorship and correct citation details are given, and that the bibliographic details are not changed. If the article/book is reproduced or disseminated in part, this must be clearly and unequivocally indicated. Springer is committed permanently to maintaining this open access publishing policy, retrospectively and prospectively, in all eventualities, including any future changes in ownership.

Share

COinS