System Identification Based on Mutual Information Criteria

As a central concept in communication theory, mutual information measures the amount of information that one random variable contains about another. The larger the mutual information between two random variables is, the more information they share, and the better the estimation algorithm can be. Typically, there are two mutual information-based identification criteria: the minimum mutual information (MinMI) and the maximum mutual information (MaxMI) criteria. The MinMI criterion tries to minimize the mutual information between the identification error and the input signal such that the error signal contains as little as possible information about the input,1 while the MaxMI criterion ...

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