Applied Mathematics & Information Sciences

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This paper is concerned with the class of uncertain discrete time Bi-directional associative memory (BAM) cellular neural networks with variable delays. Here the result is enhanced to ensure the global stability in the sense of exponential for the addressed time delayed neural networks by employing a discrete analogue of Halanay-type inequality. This type of inequalities can be used as basic tool in the study of exponential stability of the equilibrium for certain generalized difference equations. An important feature presents in our paper is that, with the help of time-invariant perturbation matrix which is often called parameter uncertainties, the proposed stability conditions can be proved. [(i.e) It is allowed to be norm-bounded]. At last, three illustrative examples with simulations are provided for the addressed neural networks to demonstrate the usefulness and flexibility of the proposed design approach.

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