Fault Data Compression of Power System with Wavelet Neural Network Based on Wavelet Entropy

  • Zhigang Liu
  • Dabo Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


Through the analysis of function approximation with wavelet transformation, an adaptive wavelet neural network is introduced in the paper, which is applied in data compression of fault data in power system. In addition, the wavelet entropy is adopted to choose the hidden nodes in the wavelet neural network. The learning algorithm of the wavelet neural network based on wavelet entropy is proposed and discussed for data compression of fault data in power system. The simulation results show that it is feasible and valid in the end.


Power System Wavelet Transformation Data Compression Wavelet Function Wavelet Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Zhigang Liu
    • 1
  • Dabo Zhang
    • 1
  1. 1.Institute of Electrification & AutomationSouthwest Jiaotong UniversityChengduChina

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