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A fast maximum-likelihood estimation and detection algorithm for Bernoulli-Gaussian processes

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3 Author(s)
Chi, C.Y. ; University of Southern California, Los Angeles, CA ; Goutsias, J. ; Mendel, J.M.

We derive and implement a maximum-likelihood detection and estimation algorithm based on the same channel and statistical models used by Kormylo and Mendel [1], that leads to less computations than the approach presented by Chi, Mendel and Hampson [2]. We introduce a single generalized likelihood function and we develop the Multiple-Most-Likely Replacement (MMLR) detector. This detector is computationally faster compared with the Single-Most-Likely Replacement (SMLR) detector developed by Kormylo and Mendel [3]. We demonstrate good performance of our algorithm for a synthetic data example.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '85.  (Volume:10 )

Date of Conference:

Apr 1985