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Desynchronization of Morris: Lecar Network via Robust Adaptive Artificial Neural Network

  • Yingyuan Chen
  • Jiang Wang
  • Xile Wei
  • Bin Deng
  • Haitao Yu
  • Fei Su
  • Ge Li
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

This paper has presented a robust adaptive artificial neural network (ANN) method to desynchronize a network composed of Morris–Lecar (M–L) neuron model. During the whole process of desynchronizing the network, the robust adaptive controllers play the roles of synchronizing a selected neuron in the network and a reference neuron, and desynchronizing the network with desired phase differences generated by constructing the difference between the output curve of the reference neuron and the shifted output curve of the reference neuron with desired phase difference. The method is robust and can be applied in Deep Brain Stimulation (DBS) therapies.

Keywords

Desynchronization Morris–Lecar network Artificial neural network Phase shifting 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Yingyuan Chen
    • 1
  • Jiang Wang
    • 1
  • Xile Wei
    • 1
  • Bin Deng
    • 1
  • Haitao Yu
    • 1
  • Fei Su
    • 1
  • Ge Li
    • 1
  1. 1.School of Electrical and Automation EngTianjin UniversityTianjinPeople’s Republic of China

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