DocumentCode :
2953288
Title :
General smoothing techniques for estimating deterministic sinusoidal frequencies from noisy data
Author :
Itzikowitz, Samuel ; Averbuch, Amir
Author_Institution :
Dept. of Comput. Sci., Tel-Aviv Univ., Israel
fYear :
1990
fDate :
3-6 Apr 1990
Firstpage :
2583
Abstract :
General high-resolution smoothing techniques for estimating deterministic sinusoidal frequencies from short-record noisy data are presented. These techniques are general in the sense that methods such as the modified least squares Prony method, as well as those which are based on eigenvector decompositions, may be considered as special cases of them. The theoretical basis of these smoothing techniques is discussed, and their performance in the presence of white Gaussian noise at low signal-to-noise ratio (SNR) is examined. It is shown that close to the threshold of the maximum-likelihood method (SNR≈3 dB) these symmetric smoothing techniques provide better accuracy than any other current method
Keywords :
parameter estimation; signal processing; spectral analysis; white noise; deterministic sinusoidal frequencies; eigenvector decompositions; frequency estimation; high-resolution smoothing techniques; low signal-to-noise ratio; maximum-likelihood method; modified least squares Prony method; noisy data; white Gaussian noise; Computer science; Equations; Frequency estimation; Gaussian noise; Least squares methods; Maximum likelihood estimation; Noise measurement; Numerical simulation; Polynomials; Signal to noise ratio; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.1990.116138
Filename :
116138
Link To Document :
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