Abstract
In this paper by applying vector Lyapunov function method and M matrix theory which are different from all the existing study methods (LMI technique), some sufficient conditions ensuring stochastic exponential stability of the equilibrium point of a class of Cohen-Grossberg neural networks with Markovian jumping parameters and mixed delays are derived.
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Xu, X., Zhang, J., Zhang, W. (2011). Stochastic Exponential Stability of Cohen-Grossberg Neural Networks with Markovian Jumping Parameters and Mixed Delays. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21105-8_43
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DOI: https://doi.org/10.1007/978-3-642-21105-8_43
Publisher Name: Springer, Berlin, Heidelberg
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