Cross Entropy Approximation of Structured Covariance Matrices

Details Cross Entropy Approximation of Structured Covariance Matrices Cross Entropy Approximation of Structured Covariance Matrices

2006-08-30

arxiv.org/abs/cs/0608121v1

IEEE Transactions on Signal Processing, vol. 56, issue 7, Part 2, pages 3362-3367, 2008

Computer Science

Information Theory

20 pages

Scientific paper

We apply two variations of the principle of Minimum Cross Entropy (the Kullback information measure) to fit parameterized probability density models to observed data densities. For an array beamforming problem with P incident narrowband point sources, N > P sensors, and colored noise, both approaches yield eigenvector fitting methods similar to that of the MUSIC algorithm[1]. Furthermore, the corresponding cross-entropies are related to the MDL model order selection criterion[2].

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