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Robust stability of Cohen-Grossberg neural networks via state transmission matrix.

Research paper by Zhanshan Z Wang, Huaguang H Zhang, Wen W Yu

Indexed on: 09 Jan '09Published on: 09 Jan '09Published in: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council



Abstract

This brief is concerned with the global robust exponential stability of a class of interval Cohen-Grossberg neural networks with both multiple time-varying delays and continuously distributed delays. Some new sufficient robust stability conditions are established in the form of state transmission matrix, which are different from the existing ones. Furthermore, a sufficient condition is also established to guarantee the global stability for this class of Cohen-Grossberg neural networks without uncertainties. Three examples are used to show the effectiveness of the obtained results.