DocumentCode :
805366
Title :
Two-dimensional minimum free energy spectral estimation
Author :
Kiernan, P.
Volume :
142
Issue :
3
fYear :
1995
fDate :
6/1/1995 12:00:00 AM
Firstpage :
169
Lastpage :
173
Abstract :
The author proposes a 2-D extension of the minimum free energy (MFE) parameter estimation method which may be used to determine autoregressive (AR) model parameters for 2-D spectral estimation. The performance of the technique for spectral estimation of 2-D sinusoids in white noise is demonstrated by numerical example. It is seen that MFE can provide superior spectral estimation over that which can be achieved with the multidimensional Levinson algorithm with equivalent computational burden. The performance of the technique in terms of computational expense and accuracy of spectral estimation over a number of simulation trials is compared with a modified covariance technique
Keywords :
autoregressive processes; covariance analysis; parameter estimation; spectral analysis; white noise; 2-D sinusoids; 2-D spectral estimation; autoregressive model parameters; computational expense; minimum free energy; modified covariance technique; numerical example; parameter estimation; two-dimensional estimation; white noise;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:19951802
Filename :
393294
Link To Document :
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