GLOBAL STABILITY ANALYSIS FOR A CLASS OF COHEN-GROSSBERG NEURAL NETWORK MODELS

By constructing suitable Lyapunov functionals and combin- ing with matrix inequality technique, a new simple sufficient condition is presented for the global asymptotic stability of the Cohen-Grossberg neural network models. The condition contains and improves some of the previous results in the earlier references. n ∑ j=1 a ijf j( x j( t )) + n ∑ j=1 b ijf j( x j( tj( t ))) + J i )

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