The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-222

“EVAM: An Eigenvector-Based Algorithm for Multichannel Blind Deconvolution of Input Colored Signals”

by M. I. Gurelli and C. L. Nikias

September 1992

In this paper, the development of a new algorithm is presented for the deconvolution of an unknown, possibly colored signal which is observed through two or more unknown channels described by rational system transfer functions. The algorithm not only reconstructs the input signal but also determines the roots (poles and zeros) of the multipath channels with enhanced accuracy, even in the presence of additive Gaussian noise at the channel outputs. This algorithm can also be used in multichannel system identification problems. In this paper, it is assumed that the additive noise processes at the outputs of the unknown channels are white. Results are presented for both noise-free and noisy cases.

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