Convergent activation dynamics in continuous time networks
Neural Networks
Frustration, stability, and delay-induced oscillations in a neural network model
SIAM Journal on Applied Mathematics
Stability analysis of delayed cellular neural networks
Neural Networks
Exponential stability of Cohen-Grossberg neural networks
Neural Networks
Global exponential stability of delayed Hopfield neural networks
Neural Networks
Global convergence rate of recurrently connected neural networks
Neural Computation
New conditions on global stability of Cohen-Grossberg neural networks
Neural Computation
Dynamics of periodic delayed neural networks
Neural Networks
A note on stability of analog neural networks with time delays
IEEE Transactions on Neural Networks
Stability of asymmetric Hopfield networks
IEEE Transactions on Neural Networks
Global robust stability of interval neural networks with multiple time-varying delays
Mathematics and Computers in Simulation
Multiple almost periodic solutions in nonautonomous delayed neural networks
Neural Computation
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Synchronization between Two Different Chaotic Neural Networks with Fully Unknown Parameters
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Universal analysis method for stability of recurrent neural networks with different multiple delays
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Universal approach to study delayed dynamical systems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Multistability of delayed neural networks with discontinuous activations
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
Exponential convergence of an epidemic model with continuously distributed delays
Mathematical and Computer Modelling: An International Journal
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Research of delayed neural networks with varying self-inhibitions, interconnection weights, and inputs is an important issue. In the real world, self-inhibitions, interconnection weights, and inputs should vary as time varies. In this letter, we discuss a large class of delayed neural networks with periodic inhibitions, interconnection weights, and inputs. We prove that if the activation functions are of Lipschitz type and some set of inequalities, for example, the set of inequalities 3.1 in theorem 1, is satisfied, the delayed system has a unique periodic solution, and any solution will converge to this periodic solution. We also prove that if either set of inequalities 3.20 in theorem 2 or 3.23 in theorem 3 is satisfied, then the system is exponentially stable globally. This class of delayed dynamical systems provides a general framework for many delayed dynamical systems. As special cases, it includes delayed Hopfield neural networks and cellular neural networks as well as distributed delayed neural networks with periodic self-inhibitions, interconnection weights, and inputs. Moreover, the entire discussion applies to delayed systems with constant self-inhibitions, interconnection weights, and inputs.