A recursive blind adaptive identification algorithm and its almost sure convergence

Miloje S. Radenkovic, Tamal Bose

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


This paper presents a novel blind adaptive identification algorithm based on least-squares type arguments. Parameter estimates are recursively updated with each output measurement, without resorting to any matrix inversion operation. It is proved that the parameter estimates converge almost surely (a.s.) toward a scalar multiple of the true parameters. Possible application of this algorithm to the channel equalization problem is discussed.

Original languageEnglish (US)
Pages (from-to)1380-1388
Number of pages9
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Issue number6
StatePublished - Jun 2007


  • Almost sure eigenvalue
  • Blind adaptive identification
  • Blind equalization
  • Recursive parameter estimation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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