Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
Dynamics of a class of discete-time neural networks and their comtinuous-time counterparts
Mathematics and Computers in Simulation
Discrete-time analogues of integrodifferential equations modelling bidirectional neural networks
Journal of Computational and Applied Mathematics
Exponential stability of delayed bi-directional associative memory networks
Applied Mathematics and Computation
Exponential Periodicity of Continuous-time and Discrete-Time Neural Networks with Delays
Neural Processing Letters
Exponential stability and periodic oscillatory solution in BAM networks with delays
IEEE Transactions on Neural Networks
Unsupervised learning in noise
IEEE Transactions on Neural Networks
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In this paper, a discrete-time bidirectional associative memory neural networks model is considered. By employing the theory of coincidence degree and using Halanay-type inequality technique we give some sufficient conditions ensuring the existence and globally exponential stability of periodic solutions for the discrete-time bidirectional neural networks. An example with the numerical simulations is provided to show the correctness of our analysis.