Cross Entropy Approximation of Structured Covariance Matrices
<|reference_start|>Cross Entropy Approximation of Structured Covariance Matrices: 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].<|reference_end|>
@article{liou2006cross,
    title={Cross Entropy Approximation of Structured Covariance Matrices},
    author={Cheng-Yuan Liou and Bruce R. Musicus},
    journal={IEEE Transactions on Signal Processing, vol. 56, issue 7, Part 2,
  pages 3362-3367, 2008},
    year={2006},
    archivePrefix={arXiv},
    eprint={cs/0608121},
    primaryClass={cs.IT math.IT}
}