
In this paper, an adaptive algorithm for linear instantaneous independent component analysis is proposed, which is is based on minimizing the mutual information contrast function. Adaptive density estimation by modified kernel density estimation is applied to estimate the unknown probability density functions as well as their first and second derivatives. Empirical comparisons with several popular algorithms confirm the efficiency of the proposed algorithm.
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