Analysis and comparative evaluation of techniques for multichannel blind deconvolution

G. Harikumar, Yoram Bresler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Deterministic multichannel blind deconvolution is an important problem arising in numerous areas of engineering. Recently, two different approaches to solving this problem, Maximum Likelihood techniques (like IQML) and subspace techniques (like EVAM), have been proposed. These methods are theoretically elegant and computationally efficient, and questions arise as to what the properties of these estimators are. We attempt to answer some of these questions in this paper. We show that the subspace based EVAM estimator is a coarse approximation of the IQML estimator. We present a new iterative scheme to compute the M-L estimator, and Cramer-Rao bounds for the channel and input estimates. In addition, we present a Monte-Carlo comparison study of the two estimators and establish the superiority of ML based techniques.

Original languageEnglish (US)
Title of host publicationIEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP
Editors Anon
PublisherIEEE
Pages332-335
Number of pages4
StatePublished - 1996
EventProceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96 - Corfu, Greece
Duration: Jun 24 1996Jun 26 1996

Other

OtherProceedings of the 1996 8th IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP'96
CityCorfu, Greece
Period6/24/966/26/96

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Harikumar, G., & Bresler, Y. (1996). Analysis and comparative evaluation of techniques for multichannel blind deconvolution. In Anon (Ed.), IEEE Signal Processing Workshop on Statistical Signal and Array Processing, SSAP (pp. 332-335). IEEE.