New learning algorithm for blind separation of sources

A. Cichocki, L. Moszczyński

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

A new improved, easily implementible learning algorithm for blind separation of statistically independent unknown source signals is proposed. In contrast to the well known algorithms, two time trajectories of synaptic weights {wij(t)} and {wij(t)} a r e computed where wij(t) is the time average of wif(t). Extensive computer simulation experiments have confirmed that the proposed learning algorithm assures a high convergence speed of the neural network for a blind identification problem, i.e. a quick recovering of unknown signals from the observation of a linear combination (mixture) of them. The algorithm can easily be extended to other applications.

Original languageEnglish
Pages (from-to)1986-1987
Number of pages2
JournalElectronics Letters
Volume28
Issue number21
DOIs
Publication statusPublished - Oct 1992
Externally publishedYes

Keywords

  • Learning algorithms
  • Neural networks
  • Signal processing

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