A Separable Cross-Entropy Approach to Power Spectral Estimation
Resource
IEEE Transactions on Acoustics, Speech and Signal Processing 38 (1): 105-113
Journal
IEEE Transactions on Acoustics, Speech and Signal Processing
Journal Volume
38
Journal Issue
1
Pages
105-113
Date Issued
1990
Date
1990
Author(s)
Liou, Cheng-Yuan
Musicus, Bruce R.
Abstract
An approach to power spectrum estimation that is based on a separable cross-entropy modeling procedure is presented. The authors start with a model of a multichannel, multidimensional, stationary Gaussian random process that is sampled on a nonuniform grid. An approximate separable model in which selected frequency samples of the process are modeled as independent random variables, is then fitted to it. Two cross-entropy-like criteria are used to select optimal separable approximations. One of them yields a spectral estimation algorithm that is a generalized version of Capon's maximum-likelihood method, and the other is similar to classical windowing methods. They discuss different strategies for designing bandpass filters for use with the cross-entropy approach.>
Type
journal article
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