A nonlinear recursive least-squares algorithm for the blind separation of finite-alphabet sources

Scott C. Douglas, S. Y. Kung

Research output: Contribution to journalConference article

Abstract

In this paper, we present an adaptive algorithm that blindly separates mixtures of finite-alphabet sources given knowledge of the source alphabet and distribution. The algorithm is a nonlinear recursive least-squares procedure that employs a simple and numerically-robust square root House-holder update. Simulations verify that the algorithm can separate large-scale noisy mixtures of finite-alphabet sources without any knowledge of the number of sources in the mixture.

Original languageEnglish (US)
Pages (from-to)729-732
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
StatePublished - Sep 25 2003
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: Apr 6 2003Apr 10 2003

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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