DocumentCode
3474137
Title
A novel cyclic algorithm for maximum likelihood frequency estimation
Author
Shaw, Amab Kumar
Author_Institution
Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA
fYear
1993
fDate
1-3 Aug. 1993
Firstpage
412
Lastpage
415
Abstract
An algorithm for estimation of frequencies of narrowband sources from noisy observation data is presented. For Gaussianly distributed noise, the algorithm produces maximum likelihood estimates, otherwise least-squares estimates, are obtained. The proposed algorithm is iterative, and at each step of iteration the optimization is with respect to a single frequency only, and hence simple hardware/software is sufficient for implementation. The performance of the algorithm has been compared with theoretical Cramer-Rao bounds.<>
Keywords
iterative methods; least squares approximations; optimisation; parameter estimation; signal processing; Cramer-Rao bounds; Gaussianly distributed noise; cyclic algorithm; iterative methods; least squares approximations; least-squares estimates; maximum likelihood frequency estimation; narrowband sources; noisy observation data; optimization; parameter estimation; signal processing; Iterative methods; Least squares methods; Optimization methods; Parameter estimation; Signal processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems Engineering, 1991., IEEE International Conference on
Conference_Location
Dayton, OH, USA
Print_ISBN
0-7803-0173-0
Type
conf
DOI
10.1109/ICSYSE.1991.161165
Filename
161165
Link To Document