Variable-delay feedback control for stabilisation of highly nonlinear hybrid stochastic neural networks with time-varying delays
Ailong Wu, Han Yu, Zhigang Zeng
Abstract
A new highly nonlinear hybrid stochastic neural network with variable time delays is formulated, which is usually found to be unstable. In addition, the network coefficients considered in this article grow polynomially rather than linearly as we always considered before. Since original system is unstable, the purpose of this article is to construct a variable-delay feedback control function to make the augmented system stable. Then, four results on the stabilisation of the controlled system are given separately. At last, an example is provided to display the feasibility of theoretical results.
Topics & Concepts
Control theory (sociology)Artificial neural networkVariable (mathematics)Nonlinear systemControl (management)Computer scienceFeedback controlFunction (biology)Stochastic neural networkStability (learning theory)MathematicsControl engineeringEngineeringRecurrent neural networkArtificial intelligencePhysicsMathematical analysisBiologyMachine learningQuantum mechanicsEvolutionary biologyNeural Networks Stability and Synchronizationstochastic dynamics and bifurcationNeural Networks and Applications