Open AccessStability and bifurcation control in inertial neuron networks with delays
Author(s) -
Linhe Zhu,
Hongyong Zhao
Publication year - 2014
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.63.090203
Subject(s) - control theory (sociology) , hopf bifurcation , bifurcation , controller (irrigation) , inertial frame of reference , stability (learning theory) , biological applications of bifurcation theory , convergence (economics) , inertia , computer science , artificial neural network , bifurcation theory , bifurcation diagram , delay differential equation , saddle node bifurcation , mathematics , control (management) , differential equation , nonlinear system , physics , mathematical analysis , classical mechanics , quantum mechanics , artificial intelligence , machine learning , agronomy , economics , biology , economic growth
Based on the second order delay inertia neural network model, this paper puts forward the bifurcation control method: delay feedback control method. Applying the theory of delay differential equations, we give some stability and Hopf bifurcation conditions for the feedback control system. Examples are given to validate that the feedback controller can control the occurrence of bifurcation effectively, expand the stability domain, and change the convergence speed of the network as well.