Nonlinear system identification using multi-resolution reproducing kernel based support vector regression

Abstract

A new reproducing kernel in reproducing kernel Hubert space (RKHS), namely the multi-resolution reproducing kernel, is presented in this paper, The multi-resolution reproducing kernel is generated by scaling basis function at some scale and wavelet basis function with different resolution. Based on multi-resolution reproducing kernel and v- support vector regression (v-SVR) method, a new regression model is proposed. The regression model used to nonlinear system identification, incorporate the advantage of the support vector machines and the multi-resolution property of wavelet. Simulation examples are given to illustrate the feasibility and effectiveness of the method. © Springer-Verlag Berlin Heidelberg 2006.