Publication:
On the convergence of symmetrically orthogonalized bounded component analysis algorithms for uncorrelated source separation

Placeholder

Program

KU Authors

Co-Authors

Advisor

Publication Date

Language

English

Journal Title

Journal ISSN

Volume Title

Abstract

Bounded Component Analysis (BCA) has recently been introduced as an alternative linear decomposition scheme. In this approach the boundedness property of sources is exploited to replace the usual independence assumption with a weaker assumption, which enables development of methods to separate both independent and dependent components from their mixtures. This paper positions total output range minimization based blind source separation approach as a BCA method for the separation of uncorrelated sources. It is shown that the global minimizers of the corresponding optimization problem are the perfect separators. Furthermore, a stationary point analysis for the corresponding algorithms based on symmetrical orthogonalization is provided. The main result of this analysis is that the range minimization based parallel BCA algorithm and the kurtosis maximization based Independent Component Analysis algorithm have related set of identified stationary points.

Description

Source:

IEEE Transactions on Signal Processing

Publisher:

IEEE-Inst Electrical Electronics Engineers Inc

Keywords:

Subject

Engineering, Electrical electronic engineering

Citation

Endorsement

Review

Supplemented By

Referenced By

Copy Rights Note

0

Views

0

Downloads

View PlumX Details