A modified infomax algorithm for blind signal separation

We present a new algorithm to perform blind signal separation (BSS), which takes a trade-off between the ordinary gradient infomax algorithm and the natural gradient infomax algorithm. Analyzing the algorithm, we show that desired equilibrium points are locally stable by choosing appropriate score functions and step sizes. The algorithm provides better performance than the ordinary gradient algorithm, and it is free from approximation error and the small-step-size restriction of the natural gradient algorithm. In simulations on convolved mixtures, the algorithm provides much better performance than the other algorithms while requiring less computation. (c) 2006 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2006-12
Language
ENG
Keywords

INDEPENDENT COMPONENT ANALYSIS; ADAPTIVE SOURCE SEPARATION

Citation

NEUROCOMPUTING, v.70, no.1-3, pp.229 - 240

ISSN
0925-2312
DOI
10.1016/j.neucom.2006.03.009
URI
http://hdl.handle.net/10203/10205
Appears in Collection
EE-Journal Papers(저널논문)
  • Hit : 207
  • Download : 2
  • Cited 0 times in thomson ci
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡClick to seewebofscience_button
⊙ Cited 2 items in WoSClick to see citing articles inrecords_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0