A novel blind deconvolution method via maximum entropy

Monika Pinchas; Ben Zion Bobrovsky

doi:10.1109/ssp.2005.1628619

A novel blind deconvolution method via maximum entropy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We propose a new closed form (approximated) expression for the conditional expectation that is based on Maximum Entropy. This expression does not rely on the knowledge of the convolutional noise power nor imposes any restrictions on the probability distribution of the unobserved input sequence and is suitable for the general case of real and complex source signals. In addition, we propose a set of algebraic linear equations for the Lagrange multipliers related to the blind deconvolution problem that can be easily computed in a non iterative approach. Our new derivation leads to a new blind deconvolution algorithm with improved equalization performance compared with Godard's equalizer.

Original language	English
Title of host publication	2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts
Publisher	IEEE Computer Society
Pages	351-356
Number of pages	6
ISBN (Print)	0780394046, 9780780394049
DOIs	https://doi.org/10.1109/ssp.2005.1628619
State	Published - 2005
Externally published	Yes
Event	2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Bordeaux, France Duration: 17 Jul 2005 → 20 Jul 2005

Publication series

Name	IEEE Workshop on Statistical Signal Processing Proceedings
Volume	2005

Conference

Conference	2005 IEEE/SP 13th Workshop on Statistical Signal Processing
Country/Territory	France
City	Bordeaux
Period	17/07/05 → 20/07/05

Access to Document

10.1109/ssp.2005.1628619

Cite this

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title = "A novel blind deconvolution method via maximum entropy",

abstract = "We propose a new closed form (approximated) expression for the conditional expectation that is based on Maximum Entropy. This expression does not rely on the knowledge of the convolutional noise power nor imposes any restrictions on the probability distribution of the unobserved input sequence and is suitable for the general case of real and complex source signals. In addition, we propose a set of algebraic linear equations for the Lagrange multipliers related to the blind deconvolution problem that can be easily computed in a non iterative approach. Our new derivation leads to a new blind deconvolution algorithm with improved equalization performance compared with Godard's equalizer.",

author = "Monika Pinchas and Bobrovsky, {Ben Zion}",

year = "2005",

doi = "10.1109/ssp.2005.1628619",

language = "אנגלית",

isbn = "0780394046",

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publisher = "IEEE Computer Society",

pages = "351--356",

booktitle = "2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts",

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note = "2005 IEEE/SP 13th Workshop on Statistical Signal Processing ; Conference date: 17-07-2005 Through 20-07-2005",

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Pinchas, M & Bobrovsky, BZ 2005, A novel blind deconvolution method via maximum entropy. in 2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts., 1628619, IEEE Workshop on Statistical Signal Processing Proceedings, vol. 2005, IEEE Computer Society, pp. 351-356, 2005 IEEE/SP 13th Workshop on Statistical Signal Processing, Bordeaux, France, 17/07/05. https://doi.org/10.1109/ssp.2005.1628619

A novel blind deconvolution method via maximum entropy. / Pinchas, Monika; Bobrovsky, Ben Zion.
2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts. IEEE Computer Society, 2005. p. 351-356 1628619 (IEEE Workshop on Statistical Signal Processing Proceedings; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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A novel blind deconvolution method via maximum entropy

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