Blind extraction of singularly mixed source signals

Yuanqing Li, Jun Wang, Jacek M. Zurada

Research output: Contribution to journalArticlepeer-review

46 Citations (Scopus)

Abstract

This paper introduces a novel technique for sequential blind extraction of singularly mixed sources. First, a neural-network model and an adaptive algorithm for single-source blind extraction are introduced. Next, extractability analysis is presented for singular mixing matrix, and two sets of necessary and sufficient extractability conditions are derived. The adaptive algorithm and neural-network model for sequential blind extraction are then presented. The stability of the algorithm is discussed. Simulation results are presented to illustrate the validity of the adaptive algorithm and the stability analysis. The proposed algorithm is suitable for the case of nonsingular mixing matrix as well as for singular mixing matrix.

Original languageEnglish
Pages (from-to)1413-1422
Number of pages10
JournalIEEE Transactions on Neural Networks
Volume11
Issue number6
DOIs
Publication statusPublished - 2000
Externally publishedYes

Keywords

  • Adaptive algorithm
  • Blind extraction
  • Extractability
  • Singular matrix
  • Stability

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