Brains, machines, and mathematics (2nd ed.)
Brains, machines, and mathematics (2nd ed.)
Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Impulsive stabilization of functional differential equations by Lyapunov-Razumikhin functions
Nonlinear Analysis: Theory, Methods & Applications
Exponential stability of delayed bi-directional associative memory networks
Applied Mathematics and Computation
Global asymptotic stability of delayed bi-directional associative memory neural networks
Applied Mathematics and Computation
Journal of Computational and Applied Mathematics
Exponential stability and periodic oscillatory solution in BAM networks with delays
IEEE Transactions on Neural Networks
How delays affect neural dynamics and learning
IEEE Transactions on Neural Networks
Delay-independent stability in bidirectional associative memory networks
IEEE Transactions on Neural Networks
Bidirectional associative memories: Different approaches
ACM Computing Surveys (CSUR)
On asymptotic stability in impulsive semidynamical systems
Journal of Dynamical and Control Systems
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In this paper, we study the problem of global asymptotic stability for a class of bidirectional associative memory neural networks with distributed delays and nonlinear impulsive operators. We establish stability criteria by employing Lyapunov functions and the Razumikhin technique. These results can easily be used to design and verify globally stable networks. An illustrative example is given to demonstrate the effectiveness of the obtained results.