The hidden neurons selection of the wavelet networks using support vector machines and ridge regression

被引：25
|
作者：
Han, Min [1 ]
Yin, Jia [1 ]
机构：
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116023, Peoples R China
来源：
NEUROCOMPUTING | 2008年 / 72卷 / 1-3期
关键词：
Wavelet network; Support vector machine; Hidden neurons selection; Ridge regression;
D O I：
10.1016/j.neucom.2007.12.009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A 1-norm support vector machine stepwise (SVMS) algorithm is proposed for the hidden neurons selection of wavelet networks (WNs). In this new algorithm, the linear programming support vector machine (LPSVM) is employed to pre-select the hidden neurons, and then a stepwise selection algorithm based on ridge regression is introduced to select hidden neurons from the pre-selection. The main advantages of the new algorithm are that it can get rid of the influence of the ill conditioning of the matrix and deal with the problems that involve a great number of candidate neurons or a large size of samples. Four examples are provided to illustrate the efficiency of the new algorithm. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码：471 / 479
页数：9
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