DocumentCode :
1103942
Title :
Maximum entropy spectral estimation for regular time series of degenerate rank
Author :
Inouye, Yujiro
Author_Institution :
Osaka University, Toyonaka, Osaka, Japan
Volume :
32
Issue :
4
fYear :
1984
fDate :
8/1/1984 12:00:00 AM
Firstpage :
733
Lastpage :
740
Abstract :
This paper deals with multichannel time series of degenerate rank, and extends the maximum entropy method over the degenerate rank case. In order to define the entropy of a multichannel time series of degenerate rank, we must first clarify all the deterministic relationships in the time series. This will be done for any regular time series matching given finite data {R_{0}, R_{1},..., R_{n}} of the autocorrelation sequence \\{R_{k}\\}_{-\\infty}^{\\infty} . A necessary and sufficient condition of the existence of a regular time series matching the data will be presented. Next, the entropy Hm(P) of a time series with its power spectrum P(ω) of rank less than equal to m is defined by H_{m}(P) =\\int_{\\hbox{-}\\pi}^{\\pi} \\log S_{m}[P(\\omega )] d\\omega where Sm[P] denotes the sum of all the principal minors of order m of the matrix P. The main purpose of this paper is to show that the maximum entropy power spectrum (i.e., the power spectrum which maximizes the entropy) is identical with the autoregressive power spectrum (i.e., the power spectrum obtained by the autoregressive fitting) even in the degenerate rank case.
Keywords :
Autocorrelation; Control engineering; Data mining; Entropy; Feedback control; Feedback loop; Marine vehicles; Power generation; Predictive models; Sufficient conditions;
fLanguage :
English
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
0096-3518
Type :
jour
DOI :
10.1109/TASSP.1984.1164393
Filename :
1164393
Link To Document :
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