Varying scales wavelet neural network based on entropy function and its application in channel equalization

  • Authors:

  • Mingyan Jiang;Dongfeng Yuan;Shouliang Sun

  • Affiliations:

  • School of Information Science and Engineering, Shandong University, Jinan, Shandong, China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, China;School of Information Science and Engineering, Shandong University, Jinan, Shandong, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
  • Year:
  • 2005

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Abstract

This paper proposes a new kind of neural network named varying scales wavelet neural network to reduce wavelet-neuron number and simplify network structure. In order to avoid the local minima, entropy function is used as penalty function. The new network is applied to channel equalization, simulation results demonstrate that this network has less wavelet-neurons and recursive steps and can converge to the global minimum.