Improved Techniques for Blind Source Separation

DOI

10.2991/icecee-15.2015.2How to use a DOI?

Keywords

Separation; Factor; Matrix; Distribution; Recovery; Independence.

Abstract

In many practical applications such as biomedical signal processing, it is often desirable to extract one or a few source signals instead of all signals. The classical FASTICA algorithm can extract a source signal which has the maximum negentropy of all signals. However, the extracted signal is not necessarily the desired one. To address these problems above, a constraint is introduced to a negentropy based cost function. As a result, a constrained method is proposed which can extract a desired signal from its mixture exclusively.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yongjian Zhao
PY  - 2015/06
DA  - 2015/06
TI  - Improved Techniques for Blind Source Separation
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 5
EP  - 8
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.2
DO  - 10.2991/icecee-15.2015.2
ID  - Zhao2015/06
ER  -