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

Scott C. Douglas; S. Y. Kung

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

Scott C. Douglas, S. Y. Kung

Research output: Contribution to journal › Conference article › peer-review

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 language	English (US)
Pages (from-to)	729-732
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	2
State	Published - 2003
Event	2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong Duration: Apr 6 2003 → Apr 10 2003

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Electrical and Electronic Engineering

Cite this

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title = "A nonlinear recursive least-squares algorithm for the blind separation of finite-alphabet sources",

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.",

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AU - Douglas, Scott C.

AU - Kung, S. Y.

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AB - 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.

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M3 - Conference article

AN - SCOPUS:0141676596

SN - 1520-6149

VL - 2

SP - 729

EP - 732

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing

Y2 - 6 April 2003 through 10 April 2003

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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