Behaviour analysis of adaptive ARMA predictors with nonstationary inputs

Author

M´Sirdi, N. ; Macchi, O. ; Zarader, J.

Author_Institution

Lab. de Robotique, Univ. Pierre et Marie Curie, Paris, France

fYear

1990

fDate

3-6 Apr 1990

Firstpage

1819

Abstract

The behavior of autoregressive moving average (ARMA) predictors is analyzed for neglected dynamic cases with nonstationary signals. For this analysis, nonstationarity types must be considered (abrupt or smooth changes in the mean and variance). Some procedures can be used to improve the algorithm performances and limit the self-stabilization oscillations. The resulting algorithm is not much more complex than the NLMS algorithm and can be used for applications like ADPCM or data compression with highly nonstationary signals

Keywords

adaptive systems; data compression; filtering and prediction theory; pulse-code modulation; ADPCM; adaptive ARMA predictors; algorithm performances; autoregressive moving average; data compression; dynamic cases; nonstationary inputs; nonstationary signals; self-stabilization oscillations; Algorithm design and analysis; Analysis of variance; Data compression; Error correction; Estimation error; Least squares approximation; Narrowband; Predictive models; Pulse modulation; Robots; Signal analysis; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115845

Filename

115845