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Neural Processing Letters
Published in: Neural Processing Letters 3/2019

15-02-2019

Global Exponential Synchronization of Delayed Complex-Valued Recurrent Neural Networks with Discontinuous Activations

Authors: Lian Duan, Min Shi, Zengyun Wang, Lihong Huang

Published in: Neural Processing Letters | Issue 3/2019

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Abstract

In this paper, we are concerned with the exponential synchronization for a class of two delayed complex-valued recurrent neural networks (CVRNNs) with discontinuous neuron activations. By separating CVRNNs into real and imaginary parts, forming an equivalent real-valued subsystems, under the framework of differential inclusions, novel state feedback controllers are designed and novel criteria are established to ensure the exponential stability of error system, and thus the drive system exponentially synchronize with the response system. The obtained results are essentially new and complement previously known ones. The practicability of theoretical results is also supported via a numerical example.
previous article Two-Stage Method for Diagonal Recurrent Neural Network Identification of a High-Power Continuous Microwave Heating System
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Metadata
Title
Global Exponential Synchronization of Delayed Complex-Valued Recurrent Neural Networks with Discontinuous Activations
Authors
Lian Duan
Min Shi
Zengyun Wang
Lihong Huang
Publication date
15-02-2019
Publisher
Springer US
Published in
Neural Processing Letters / Issue 3/2019
Print ISSN: 1370-4621
Electronic ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-018-09970-8

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