Abstract
This paper is concerned with the Global Asymptotic Stability (GAS) of a general class of Cohen-Grossberg neural networks with both multiple time varying delays and distributed delays. Criteria are established to ensure the GAS of the concerned neural networks, which can be expressed in the form of Linear Matrix Inequality and independent of amplification functions. Furthermore, a sufficient condition guaranteeing the global robust stability is established for the general class of Cohen-Grossberg neural networks with both multiple time varying delays and distributed delays in the case of parameter uncertainties.
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