DocumentCode
431879
Title
Wavelet-based Bayesian analysis of generalized long-memory process
Author
Gonzaga, Alex ; Kawanaka, Akira
Author_Institution
Dept. of Electr. & Electron. Eng., Sophia Univ., Tokyo, Japan
Volume
4
fYear
2005
fDate
18-23 March 2005
Abstract
In this paper we propose a Bayesian approach to estimating the parameters and predicting future values of a generalized long-memory process utilizing the approximate likelihood function of discrete wavelet packet coefficients. This approximation does not depend on the length of the signal, but the length of the wavelet filter, which is under the control of the analyst. We illustrate our approach by an example applying simulated data.
Keywords
Bayes methods; approximation theory; filtering theory; parameter estimation; prediction theory; wavelet transforms; approximate likelihood function; discrete wavelet packet coefficients; future value prediction; generalized long-memory process; parameter estimation; wavelet filter length; wavelet-based Bayesian analysis; Autocorrelation; Autoregressive processes; Bayesian methods; Discrete wavelet transforms; Filters; Frequency; Parameter estimation; Wavelet analysis; Wavelet packets; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8874-7
Type
conf
DOI
10.1109/ICASSP.2005.1416007
Filename
1416007
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