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
fDate :
6/1/1997 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
