In this paper I describe an evolutionary wavelet network to optimize the filtering of a statistical time series into separate contributions. The wavelet base is regarded as a neural network where the network nodes are discrete wavelet transforms, the wavelon, and the network structure and parameters are selected through evolutionary techniques. With this combined approach I can separate stochastic from structural components within an optimized framework and finally I can perform optimized predictive analysis on the time series components.
Evolutionay wavelet networks for statistical time series analysis / Minerva, T.. - (2010), pp. 95-99. (Intervento presentato al convegno 10th WSEAS International Conference on Wavelet Analysis and Multirate Systems, WAMUS '10, 9th WSEAS International Conference on Non-Linear Analysis, Non-Linear Systems and Chaos, NOLASC '10 tenutosi a Sousse, tun nel 2010).
Evolutionay wavelet networks for statistical time series analysis
Minerva T.
2010
Abstract
In this paper I describe an evolutionary wavelet network to optimize the filtering of a statistical time series into separate contributions. The wavelet base is regarded as a neural network where the network nodes are discrete wavelet transforms, the wavelon, and the network structure and parameters are selected through evolutionary techniques. With this combined approach I can separate stochastic from structural components within an optimized framework and finally I can perform optimized predictive analysis on the time series components.
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