Output Synchronization in Coupled Neural Networks With and Without External Disturbances
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2017 IEEE. This paper studies the output synchronization of coupled neural networks (CNNs) as well as the effects of external disturbances. By employing matrix theory and Barbalat's Lemma, several output synchronization criteria are presented for CNNs with directed and undirected topologies, respectively. Moreover, in order to ensure the output synchronization of CNNs, two adaptive schemes to adjust the coupling weights are designed. On the other hand, we, respectively, analyze the H output synchronization of directed and undirected CNNs with external disturbances, and two adaptive strategies for updating the coupling weights are designed to guarantee the H output synchronization of CNNs. Finally, two examples of CNNs are also given to verify the proposed output synchronization criteria.