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New stability results of fractional-order Hopfield neural networks with delays

This paper aims to study delayed Hopfield neural networks with fractional-order Caputo derivative. With the help of the equivalent norm techniques and fixed point theorem, the new sufficient conditions to assure the existence, uniqueness and stability of fractional-order Hopfield neural networks with delays are obtained. Finally, the efficiency of the derived criteria is illustrated by two examples.