Estimation of nonstationary AR model using the weighted recursive least square algorithm

A new method of estimating time-varying AR models using weighted recursive least square algorithm with a variable forgetting factor is described. The variable forgetting factor is adapted to a nonstationary signal by a generalized likelihood ratio algorithm through the so-called discrimination funct...

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Vydané v:1995 International Conference on Acoustics, Speech, and Signal Processing Ročník 2; s. 1432 - 1435 vol.2
Hlavní autori: Milosavljevic, M.M., Veinovic, M.D., Kovacevic, B.D.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 1995
Predmet:
Image recognition
Image segmentation
Least squares approximation
Natural languages
Recursive estimation
Signal processing
Speech analysis
Speech coding
Speech recognition
Testing
ISBN:9780780324312, 0780324315
ISSN:1520-6149
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Popis
Shrnutí:A new method of estimating time-varying AR models using weighted recursive least square algorithm with a variable forgetting factor is described. The variable forgetting factor is adapted to a nonstationary signal by a generalized likelihood ratio algorithm through the so-called discrimination function which gives a good measure of nonstationarity. In this way we connect the results from the areas of nonstationary signal estimation and jump detection, and obtain an algorithm which exhibits a good tracking performance together with a high parameter estimation accuracy. The feasibility of the approach is demonstrated with both simulation data and real speech signals.
ISBN:9780780324312
0780324315
ISSN:1520-6149
DOI:10.1109/ICASSP.1995.480552