Wavelet Kernel Based on Identification for Nonlinear Hybrid Systems

Hamid Nourisola

Abstract


This paper presents a new method based on wavelet for a class of nonlinear hybrid systems identification. Hybrid systems identification is composed of two problems; estimate the discrete modes or switch among the system modes and estimate continues submodels. In this paper, we assumed that haven’t any prior knowledge about data classification and submodels identification. Also the combining of feature vector selection algorithm and wavelet are used in subspace learning and support vector machine as a classifier. The results indicate that the error of using the wavelet in subspace learning process becomes low. In addition, the proposed method is convergent and has an acceptable response in presence of high-power noise.

Keywords


Hybrid system identification; Wavelet kernel function; Feature vector selection; Support vector machine classifier

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DOI: http://doi.org/10.11591/ijeecs.v12.i7.pp5235-5243

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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