A novel orthonormal wavelet network for function learning

  • Authors:

  • Xieping Gao;Jun Zhang

  • Affiliations:

  • Member, IEEE, Information Engineering College, Xiangtan University, Xiangtan, China;Member, IEEE, Information Engineering College, Xiangtan University, Xiangtan, China

  • Venue:
  • ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
  • Year:
  • 2005

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Abstract

This paper proposed a novel self-adaptive wavelet network model for Regression Analysis. The structure of this network is distinguished from those of the present models. It has four layers. This model not only can overcome the structural redundancy which the present wavelet network cannot do, but also can solve the complicated problems respectively. Thus, generalization performance has been greatly improved; moreover, rapid learning can be realized. Some experiments on regression analysis are presented for illustration. Compared with the existing results, the model reaches a hundredfold improvement in speed and its generalization performance has been greatly improved.