DocumentCode
1308228
Title
A unified minimum variance spectrum-based approach for simultaneous identification of both harmonic and stationary random noise fields
Author
Sexton, Andrew ; Lyon, Donald
Author_Institution
Dept. of Mech. Eng., New Brunswick Univ., Fredericton, NB, Canada
Volume
45
Issue
6
fYear
1997
fDate
6/1/1997 12:00:00 AM
Firstpage
1659
Lastpage
1663
Abstract
The technique presented in this correspondence uses the MV spectrum´s convergence properties to identify unknown and arbitrary harmonic signal fields. The correlation sequence for the identified harmonic signal field is then combined with the observed overall correlation sequence to obtain a spectral model of the random noise field
Keywords
convergence of numerical methods; correlation methods; estimation theory; harmonic analysis; parameter estimation; random noise; spectral analysis; convergence properties; correlation sequence; harmonic random noise fields; harmonic signal fields; simultaneous identification; spectral model; spectrum estimation; stationary random noise fields; unified minimum variance spectrum-based approach; Active noise reduction; Convergence; Discrete Fourier transforms; Frequency estimation; Image processing; Maximum likelihood estimation; Noise level; Phase noise; Polynomials; Signal processing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.600009
Filename
600009
Link To Document