A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

• Kobayashi Kunikazu

  Graduate School of Science and Engineering, Yamaguchi University

• Obayashi Masanao

  Graduate School of Science and Engineering, Yamaguchi University

• Kuremoto Takashi

  Graduate School of Science and Engineering, Yamaguchi University

Bibliographic Information

Other Title

• 局所線形モデルを導入したウェーブレットニューラルネットワークのベイズ的設計法
• キョクショ センケイ モデル オ ドウニュウ シタ ウェーブレットニューラル ネットワーク ノ ベイズテキ セッケイホウ

Abstract

In general, wavelet neural networks have a problem on the curse of dimensionality, i.e. hidden units to be required are exponentially increased with a high input dimension. To solve the above problem, the wavelet neural network incorporating local linear model is proposed. On the network design, however, the number of hidden units are determined by trial and error. In the present paper, a design method based on Bayesian method is proposed for the local linear wavelet neural network. Through computer simulation, the performance of the proposed method is evaluated.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 129 (7), 1356-1362, 2009

  The Institute of Electrical Engineers of Japan

Keywords

• local linear model
• wavelet neural network
• network design
• parameter learning
• Bayesian method

Details

• CRID: 1390001204604629504
• NII Article ID: 10025101366
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss.129.1356
• ISSN: 13488155
• ISSN: 03854221
• NDL BIB ID: 10357430
• Web Site: http://id.ndl.go.jp/bib/10357430
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I10357430
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/129/7/129_7_1356/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed