ANU Computer Science Technical Reports
TR-CS-97-13
Michael K. Ng.
Blind channel identification and the eigenvalue problem of structured
matrices.
July 1997.
[POSTSCRIPT (147185 bytes)] [PDF (267487 bytes)] [EPrints archive]
Abstract: In this paper, we address the problem of
restoring a signal from its noisy convolutions with two unknown channels.
When the transfer functions of these two channels have no common factors, the
blind channel identification problem can be solved by finding the minimum
eigenvalue of the Toeplitz-like matrix and its corresponding eigenvector. We
present a fast iterative algorithm to solve the numerical solution of the
eigenvalue problem for these structured matrices and hence the channel
coefficients can be estimated efficiently. Once the channel coefficients are
available, they can be used to reconstruct the unknown signal. Preliminary
numerical results illustrate the effectiveness of the method.
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