DocumentCode :
281322
Title :
Multisignal spectral estimation using an iterative relative entropy method
Author :
Alsaka, Y.A. ; Tzannes, N.S. ; Gregory, D.M.
Author_Institution :
Dept. of Electr. Eng. & Commun. Sci., Univ. of Central Florida, Orlando, FL, USA
fYear :
1988
fDate :
11-13 Apr 1988
Firstpage :
45
Lastpage :
49
Abstract :
A generalization of a method of spectral estimation by M.A. Tzaness, Ch. Moussas, and N.S. Tzannes (1984) is presented. The algorithm extends the method to the multiple signals case while still using an iterative procedure of the relative entropy method for estimating the spectral densities of the multisignal input data. Several current methods of relative entropy spectral estimation which involve solving N nonlinear equations simultaneously are also presented. The performance of the presented algorithm is compared to the maximum-entropy and other relative entropy methods, in terms of precision and computational efficiency. Classical examples are repeated and compared between the different methods
Keywords :
iterative methods; signal processing; spectral analysis; iterative relative entropy method; maximum entropy; multiple signals case; multisignal spectral estimation; Autocorrelation; Entropy; Filters; Gaussian noise; Iterative algorithms; Iterative methods; Lagrangian functions; Nonlinear equations; Signal processing; Time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Southeastcon '88., IEEE Conference Proceedings
Conference_Location :
Knoxville, TN
Type :
conf
DOI :
10.1109/SECON.1988.194813
Filename :
194813
Link To Document :
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