H∞ output synchronization of directed coupled reaction-diffusion neural networks via event-triggered quantized control

By designing a quantized controller based on event trigger, this paper considers the problem of H-infinity output synchronization for coupled neural networks with reaction-diffusion term and directed topology. Firstly, in this hybrid control strategy, the data is sampled in time domain to exclude the Zeno-behavior before judging whether an event is triggered, and then the event-triggered data instead of the sampling data itself is quantized by a logarithmic quantizer. Secondly, some sufficient conditions for H-infinity output synchronization are obtained, in which the dimension of these conditions can be reduced to only depend on the number of neurons, but not on the number of nodes. Finally, a numerical example is given to verify the theoretical results. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.