Abstract
This work presents a new sufficient condition for the uniqueness and global asymptotic stability (GAS) of the equilibrium point for a larger class of neural networks with time varying delays. It is shown that the use of a more general type of Lyapunov-Krasovskii functional leads to establish global asymptotic stability of a larger class of delayed neural networks that the neural network model considered in some previous papers.
Keywords
Exponential stability
Uniqueness
Artificial neural network
Equilibrium point
Class (philosophy)
Control theory (sociology)
Stability (learning theory)
Applied mathematics
Mathematics
Work (physics)
Lyapunov function
Point (geometry)
Computer science
Nonlinear system
Differential equation
Mathematical analysis
Artificial intelligence
Control (management)
Engineering
Physics
Machine learning
Subject Areas
Neural Networks Stability and Synchronization
·Computer Networks and Communications ·Physical Sciences
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
stochastic dynamics and bifurcation
·Statistical and Nonlinear Physics ·Physical Sciences
Citations by Year
2021: 1
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