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Global dissipativity of continuous-time recurrent neural networks with time delay
1Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Abstract:
This paper addresses the global dissipativity of a general class of continuous-time recurrent neural networks. First, the concepts of global dissipation and global exponential dissipation are defined and elaborated. Next, the sets of global dissipativity and global exponentially dissipativity are characterized using the parameters of recurrent neural network models. In particular, it is shown that the Hopfield network and cellular neural networks with or without time delays are dissipative systems.