Topics in matrix analysis
Convergence Analysis of Recurrent Neural Networks (Network Theory and Applications, V. 13)
Convergence Analysis of Recurrent Neural Networks (Network Theory and Applications, V. 13)
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
Exponential stability and periodic oscillatory solution in BAM networks with delays
IEEE Transactions on Neural Networks
Absolute exponential stability of a class of continuous-time recurrent neural networks
IEEE Transactions on Neural Networks
Delay-independent stability in bidirectional associative memory networks
IEEE Transactions on Neural Networks
Neural Processing Letters
New delay-dependent exponential stability criteria of BAM neural networks with time delays
Mathematics and Computers in Simulation
Robust stability of uncertain fuzzy Cohen-Grossberg BAM neural networks with time-varying delays
Expert Systems with Applications: An International Journal
Neural Processing Letters
Mathematics and Computers in Simulation
WSEAS Transactions on Mathematics
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
International Journal of Applied Mathematics and Computer Science
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
New results for global stability of cohen-grossberg neural networks with discrete time delays
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
New results concerning the exponential stability of delayed neural networks with impulses
Computers & Mathematics with Applications
Neural Processing Letters
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This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with fixed time delays. The results impose constraint conditions on the network parameters of neural system independent of the delay parameters. The results are applicable to all continuous non-monotonic neuron activation functions. The results are also compared with the previously reported results in the literature, implying that the results obtained in this paper provide one more set of criteria for determining the stability of bidirectional associative memory neural networks with time delays.