2003Unpublished venueRequires access

FREQUENCY DOMAIN REALIZATION OF A MULTICHANNEL BLIND DECONVOLUTION ALGORITHM BASED ON THE NATURAL GRADIENT

M. Joho, Philip Schniter

Open publisher page 31 citations

Abstract

This paper describes two efficient realizations of an adaptive multichannel blind deconvolution algorithm based on the natural gradient algorithm originally proposed by Amari, Douglas, Cichocki, and Yang. The proposed algorithms use fast convolution and correlation techniques and operate primarily in the frequency domain. Since the cost function minimized by the algorithms is welldefined in the time domain, the algorithms do not suffer from the so-called frequency-domain permutation problem. The proposed algorithm can be viewed as an multi-channel extension of a singlechannel blind deconvolution algorithm recently proposed by the authors. 1.

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What this paper is about

This paper describes two efficient realizations of an adaptive multichannel blind deconvolution algorithm based on the natural gradient algorithm originally proposed by Amari, Douglas, Cichocki, and Yang. The proposed algorithms use fast convolution and correlation techniques and operate primarily in the frequency domain. Since the cost function minimized by the algorithms is welldefined in the time domain, the algorithms do not suffer from the so-called frequency-domain permutation problem. The proposed algorithm can be viewed as an multi-channel extension of a singlechannel blind deconvolution algorithm recently proposed by the authors. 1.

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OpenAlex reports 31 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper describes two efficient realizations of an adaptive multichannel blind deconvolution algorithm based on the natural gradient algorithm originally proposed by Amari, Douglas, Cichocki, and Yang. The proposed algorithms use fast convolution and correlation techniques and operate primarily in the frequency domain. Since the cost function minimized by the algorithms is welldefined in the time domain, the algorithms do not suffer from the so-called frequency-domain permutation problem. The proposed algorithm can be viewed as an multi-channel extension of a singlechannel blind deconvolution algorithm recently proposed by the authors. 1.

Key concepts: Blind deconvolution, Deconvolution, Algorithm, Convolution (computer science), Frequency domain, Wiener deconvolution, Realization (probability), Mathematics

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