Cross Entropy Approximation of Structured Covariance Matrices Export

@misc{citeulike:822742, abstract = {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].}, archivePrefix = {arXiv}, author = {Liou, Cheng-Yuan and Musicus, Bruce R.}, citeulike-article-id = {822742}, citeulike-linkout-0 = {http://arxiv.org/abs/cs.IT/0608121}, citeulike-linkout-1 = {http://arxiv.org/pdf/cs.IT/0608121}, day = {30}, eprint = {cs.IT/0608121}, keywords = {approximation, covariance, cross-entropy, kullback, machine-learning, probability-density}, month = {Aug}, posted-at = {2006-08-31 08:07:16}, priority = {3}, title = {Cross Entropy Approximation of Structured Covariance Matrices}, url = {http://arxiv.org/abs/cs.IT/0608121}, year = {2006} }

TY - ELEC ID - citeulike:822742 L3 - citeulike-article-id:822742 N2 - 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]. TI - Cross Entropy Approximation of Structured Covariance Matrices KW - approximation KW - covariance KW - cross-entropy KW - kullback KW - machine-learning KW - probability-density AU - Liou, Cheng-Yuan AU - Musicus, Bruce PY - 2006/Aug/30/ UR - http://arxiv.org/abs/cs.IT/0608121 ER -