Sparse component analysis and blind source separation of underdetermined mixtures

Pando Georgiev, Fabian Theis, Andrzej Cichocki

Research output: Contribution to journalArticlepeer-review

298 Citations (Scopus)

Abstract

In this letter, we solve the problem of identifying matrices S ∈ ℝn×N and A ∈ ℝm×n knowing only their multiplication X = AS, under some conditions, expressed either in terms of A and sparsity of S (identifi-ability conditions), or in terms of X (sparse component analysis (SCA) conditions). We present algorithms for such identification and illustrate them by examples.

Original languageEnglish
Pages (from-to)992-996
Number of pages5
JournalIEEE Transactions on Neural Networks
Volume16
Issue number4
DOIs
Publication statusPublished - Jul 2005
Externally publishedYes

Keywords

  • Blind source separation (BSS)
  • Sparse component analysis (SCA)
  • Underdetermined mixtures

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