DocumentCode
1276089
Title
On the family of ML spectral estimates for mixed spectrum identification
Author
Sherman, Peter J. ; Lou, Kang-Ning
Author_Institution
Sch. of Mech. Eng., Purdue Univ., West Lafayette, IN, USA
Volume
39
Issue
3
fYear
1991
fDate
3/1/1991 12:00:00 AM
Firstpage
644
Lastpage
655
Abstract
A recently developed point spectrum identification procedure based on a family of AR and ML spectral estimates is exploited to arrive at a mixed spectrum identification procedure. To this end, a variety of properties of the AR and ML estimates as a function of model order are described. These properties relate to amplitude convergence, resolution and a characterization of the AR spectral artifact which is used to arrive at improved continuous spectral estimates. A variety of examples are presented
Keywords
parameter estimation; spectral analysis; AR spectral artifact; AR spectral estimates; ML spectral estimates; amplitude convergence; autoregressive estimates; characterization; maximum likelihood estimates; mixed spectrum identification; point spectrum identification procedure; resolution; Amplitude estimation; Colored noise; Convergence; Discrete Fourier transforms; Frequency estimation; Maximum likelihood estimation; Random processes; Signal to noise ratio; Spectral analysis; Testing;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.80884
Filename
80884
Link To Document