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Bifurcation and control of a class of inertial neuron networks
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The paper deals with the stability and the bifurcation of a class of inertial neural networks. Based on sensitivity theory, we determine the suitable bifurcation parameter. Using Routh-Hurwitz criterion and bifurcation theory, we give some new criteria for stability,Hopf bifurcation and steady state bifurcation. Numerieal simulations are given to validate the theoretieal analysis showing that the delayed feedback controller can control the occurrence of bifurcation effectively and the amplitude of the bifurcated limit cycle as well.
Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences
Title: Bifurcation and control of a class of inertial neuron networks
Description:
The paper deals with the stability and the bifurcation of a class of inertial neural networks.
Based on sensitivity theory, we determine the suitable bifurcation parameter.
Using Routh-Hurwitz criterion and bifurcation theory, we give some new criteria for stability,Hopf bifurcation and steady state bifurcation.
Numerieal simulations are given to validate the theoretieal analysis showing that the delayed feedback controller can control the occurrence of bifurcation effectively and the amplitude of the bifurcated limit cycle as well.
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