2002•IEEE International Conference on Acoustics Speech and Signal ProcessingRequires access

A deflation algorithm for the blind deconvolution of MIMO-FIR channels driven by fourth-order colored signals

Mitsuru Kawamoto, Yujiro Inouye, Ali Mansour, Ruey-wen Liu

Open publisher page 4 citations

Abstract

In this paper, we propose a new iterative algorithm to solve the blind deconvolution problem of MIMO-FIR channels driven by source signals which are temporally second-order uncorrelated but fourth-order correlated and spatially second- and fourth-order uncorrelated. In our new approach, to solve the blind deconvolution problem, we consider two stages: First, filtered source signals are extracted from the mixtures of source signals. Second, the source signals are recovered from the filtered source signals.

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What this paper is about

In this paper, we propose a new iterative algorithm to solve the blind deconvolution problem of MIMO-FIR channels driven by source signals which are temporally second-order uncorrelated but fourth-order correlated and spatially second- and fourth-order uncorrelated. In our new approach, to solve the blind deconvolution problem, we consider two stages: First, filtered source signals are extracted from the mixtures of source signals. Second, the source signals are recovered from the filtered source signals.

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Available abstract

In this paper, we propose a new iterative algorithm to solve the blind deconvolution problem of MIMO-FIR channels driven by source signals which are temporally second-order uncorrelated but fourth-order correlated and spatially second- and fourth-order uncorrelated. In our new approach, to solve the blind deconvolution problem, we consider two stages: First, filtered source signals are extracted from the mixtures of source signals. Second, the source signals are recovered from the filtered source signals.

Key concepts: Deconvolution, Blind deconvolution, Algorithm, MIMO, Blind signal separation, Uncorrelated, Blind equalization, Colored

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