Signal Processing - Special section: Distributed source coding
Blind Deconvolution of MIMO-IIR Systems: A Two-Stage EVA
Neural Information Processing
Non-cancellation multistage kurtosis maximization with prewhitening for blind source separation
EURASIP Journal on Advances in Signal Processing
An eigenvector algorithm with reference signals using a deflation approach for blind deconvolution
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
IEEE Transactions on Circuits and Systems Part I: Regular Papers
A study on new right/left inverses of nonsquare polynomial matrices
International Journal of Applied Mathematics and Computer Science - SPECIAL SECTION: Efficient Resource Management for Grid-Enabled Applications
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Multichannel blind deconvolution has been receiving increasing attention. Shalvi and Weinstein proposed an attractive approach to single-channel blind deconvolution called the super-exponential methods. The objective of this correspondence is to extend the Shalvi and Weinstein (1993, 1994) approach to the multichannel case and present super-exponential algorithms for multichannel blind deconvolution. We propose three approaches to multichannel blind deconvolution. In the first one, we present a multichannel super-exponential algorithm. In the second one, we present a super-exponential deflation algorithm. In the third one, we present a two-stage super-exponential algorithm