In this paper I describe an evolutionary wavelet network to optimize the filtering of a statisticaltime series into separate contributions. The wavelet base is regarded as a neural network where thenetwork nodes are discrete wavelet transforms, the wavelon, and the network structure and parameters areselected through evolutionary techniques. With this combined approach I can separate stochastic fromstructural components within an optimized framework and finally I can perform optimized predictiveanalysis on the time series components.

Evolutionary Wavelet Networks for Statistical Time Series Analysis / Minerva, T. - In: Non linear systems and wavelet analysis / A. Kallel, A. Hassairi, C. Bulucea, N. Mastorakis. - STAMPA. - Stevens Point, Wisconsin, USA : Wseas Press, 2010. - ISBN 9789604741892. - pp. 95-100

Evolutionary Wavelet Networks for Statistical Time Series Analysis

MINERVA, Tommaso
2010

Abstract

In this paper I describe an evolutionary wavelet network to optimize the filtering of a statisticaltime series into separate contributions. The wavelet base is regarded as a neural network where thenetwork nodes are discrete wavelet transforms, the wavelon, and the network structure and parameters areselected through evolutionary techniques. With this combined approach I can separate stochastic fromstructural components within an optimized framework and finally I can perform optimized predictiveanalysis on the time series components.
2010
no
Inglese
Non linear systems and wavelet analysis
95
100
9789604741892
Wseas Press
STATI UNITI D'AMERICA
Stevens Point, Wisconsin, USA
Wavelet Networks; Evolutionary Computation; Time Series Analysis
Evolutionary Wavelet Networks for Statistical Time Series Analysis / Minerva, T. - In: Non linear systems and wavelet analysis / A. Kallel, A. Hassairi, C. Bulucea, N. Mastorakis. - STAMPA. - Stevens Point, Wisconsin, USA : Wseas Press, 2010. - ISBN 9789604741892. - pp. 95-100
Minerva, Tommaso
1
Contributo su VOLUME::Capitolo/Saggio
268
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info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/642050
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