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Global Exponential Stability and Periodicity of Nonautonomous Impulsive Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms
by
Li, Kelin
, Hu, Weiyi
in
Behavior
/ Boundary conditions
/ Cellular communication
/ Fixed points (mathematics)
/ Inequality
/ Mathematical functions
/ Neural networks
/ Neurons
/ Partial differential equations
/ Poincare maps
/ Stability
/ Systems stability
2021
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Global Exponential Stability and Periodicity of Nonautonomous Impulsive Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms
by
Li, Kelin
, Hu, Weiyi
in
Behavior
/ Boundary conditions
/ Cellular communication
/ Fixed points (mathematics)
/ Inequality
/ Mathematical functions
/ Neural networks
/ Neurons
/ Partial differential equations
/ Poincare maps
/ Stability
/ Systems stability
2021
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Do you wish to request the book?
Global Exponential Stability and Periodicity of Nonautonomous Impulsive Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms
by
Li, Kelin
, Hu, Weiyi
in
Behavior
/ Boundary conditions
/ Cellular communication
/ Fixed points (mathematics)
/ Inequality
/ Mathematical functions
/ Neural networks
/ Neurons
/ Partial differential equations
/ Poincare maps
/ Stability
/ Systems stability
2021
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Global Exponential Stability and Periodicity of Nonautonomous Impulsive Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms
Journal Article
Global Exponential Stability and Periodicity of Nonautonomous Impulsive Neural Networks with Time-Varying Delays and Reaction-Diffusion Terms
2021
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Overview
In this paper, we investigate the global exponential stability and periodicity of nonautonomous cellular neural networks with reaction-diffusion, impulses, and time-varying delays. By establishing a new differential inequality for nonautonomous systems, using the properties of M-matrix and inequality techniques, some new sufficient conditions for the global exponential stability of the system are obtained. Moreover, sufficient conditions for the periodic solutions of the system are obtained by using the Poincare mapping and the fixed point theory. The validity and superiority of the main results are verified by numerical examples and simulations.
Publisher
Hindawi,John Wiley & Sons, Inc,Wiley
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