Global attractivity in delayed Hopfield neural network models
SIAM Journal on Applied Mathematics
Global exponential stability of delayed Hopfield neural networks
Neural Networks
Nonlinear Analysis: Theory, Methods & Applications
Global stability of cellular neural networks with constant and variable delays
Nonlinear Analysis: Theory, Methods & Applications
Dynamics of periodic delayed neural networks
Neural Networks
Global stability analysis of a class of delayed cellular neural networks
Mathematics and Computers in Simulation
Delay-independent stability in bidirectional associative memory networks
IEEE Transactions on Neural Networks
Applied Functional Analysis: Applications to Mathematical Physics
Applied Functional Analysis: Applications to Mathematical Physics
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This paper is concerned with the existence and global convergence of a periodic solution of delayed neural networks. Employing Schauder fixed point theorem, we obtain some novel sufficient conditions ensuring the existence as well as the global convergence of the periodic solution. Our results are new and improve some previously known results since these results are based on integral average values of the coefficients. The theoretical analysis is verified by numerical simulations.