DocumentCode :
793817
Title :
Power-spectrum identification in terms of rational models
Author :
Tretter, S.A. ; Steiglitz, K.
Author_Institution :
University of Maryland, College Park, MD, USA
Volume :
12
Issue :
2
fYear :
1967
fDate :
4/1/1967 12:00:00 AM
Firstpage :
185
Lastpage :
188
Abstract :
A technique is described for the identification of unknown power-spectral densities from sampled data in terms of a rational function of z . The problem is reduced to the minimization of a function of K parameters, where K is the order of the numerator of the model. This criterion, called the "minimum residual" criterion, reduces to the maximum likelihood criterion when the observed signal is Gaussian. A computational technique is described for minimizing this function which uses filtering and correlation to obtain the gradient and an iterative descent method due to M. J. D. Powell for minimization. Some computational results are given in which the method is compared with all-pole and conventional spectrum estimation techniques.
Keywords :
Spectral estimation; System identification; Adaptive control; Band pass filters; Frequency estimation; Matrix converters; Open loop systems; Optimal control; Parametric statistics; Process control; Regulators; Transfer functions;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1967.1098544
Filename :
1098544
Link To Document :
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