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
fDate :
3/1/1991 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on
