Signal Estimation based on Mutual Information Maximization


We study the problem of estimating signals in the presence of noise, clutter, and interference based on maximization of mutual information. Traditional approaches for signal estimation involve minimum mean squared error, maximum likelihood, minimum variance unbiased estimators, and others. The derivation of estimators for most of these, however, requires… (More)


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