The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
A blind source separation framework for detecting CPM sources mixed by a convolutive MIMO filter
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
A general algebraic algorithm for blind extraction of one source in a MIMO convolutive mixture
IEEE Transactions on Signal Processing
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Blind deconvolution and blind equalization have been important interesting topics in diverse fields including data communication, image processing, and geophysical data processing. Recently, Inouye and Habe introduced a multistage criterion for attaining blind deconvolution of multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems. In this correspondence, based on their criterion, we present iterative algorithms for solving the blind deconvolution problem of MIMO LTI systems. However, their criterion should be subjected to several constraints of equations. Therefore, they proposed a new constraint-free multistage criterion for accomplishing the blind deconvolution of MIMO LTI systems. Based on their unconstrained criterion, we show iterative algorithms for solving the blind deconvolution of multichannel LTI systems