A closed-form solution to blind equalization
Signal Processing - Special issue on higher order statistics
Blind source separation via generalized eigenvalue decomposition
The Journal of Machine Learning Research
Quadratic MIMO contrast functions for blind source separation in a convolutive context
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
IEEE Transactions on Signal Processing
Super-exponential algorithms for multichannel blind deconvolution
IEEE Transactions on Signal Processing
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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We propose an eigenvector algorithm (EVA) with reference signals for blind deconvolution (BD) of multiple-input multiple-output infinite impulse response (MIMO-IIR) channels. Differently from the conventional EVAs, each output of a deconvolver is used as a reference signal, and moreover the BD can be achieved without using whitening techniques. The validity of the proposed EVA is shown comparing with our conventional EVA.