Blind Deconvolution of MIMO-FIR Systems with Colored Inputs Using Second-Order Statistics

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概要

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• The present paper deals with the blind deconvolution of a Multiple-Input Multiple-Output Finite Impulse Response (MIMO-FIR) system. To deal with the blind deconvolution problem using the second-order statistics (SOS) of the outputs, Hua and Tugnait [7] considered it under the conditions that a) the FIR system is irreducible and b) the input signals are spatially uncorrelated and have distinct power spectra. In the present paper, the problem is considered under a weaker condition than the condition a). Namely, we assume that c) the FIR system is equalizable by means of the SOS of the outputs [11], [14]. Under b) and c), we show that the system can be blindly identified up to a permutation, a scaling, and a delay using the SOS of the outputs. Moreover, based on this identifiability, we show a novel necessary and sufficiently condition for solving the blind deconvolution problem, and then, based on the condition, we propose a new algorithm for finding an equalizer using the SOS of the outputs, while Hua and Tugnait [7] have not proposed any algorithm for solving the blind deconvolution under the conditions a) and b).

• 社団法人電子情報通信学会の論文
• 2003-03-01

著者

• Inouye Y

  Department Of Electrunic And Control Systems Engineering Shimane University

• Kawamoto M

  Department Of Electrunic And Control Systems Engineering Shimane University:bio-mitnetic Control Res

• Kawamoto Mitsuru

  Department Of Control Engineering Kyushu Institute Of Technology

• INOUE Yujiro

  Department of Electrunic and Control Systems Engineering,Shimane University

• Inoue Yujiro

  Department Of Electronic And Control Systems Engineering Shimane University

関連論文

• Blind Separation of Sources Using Temporal Correlation of the Observed Signals
• Blind Deconvolution of MIMO-FIR Systems with Colored Inputs Using Second-Order Statistics
• A Neural Net for Blind Separation of Nonstationary Signals
• Equivalence of a Cumulant Maximization Criterion for Blind Deconvolution and a Cumulant MatchingCriterion for Blind Identification

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