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

15.02.2019

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

verfasst von: Lian Duan, Min Shi, Zengyun Wang, Lihong Huang

Erschienen in: Neural Processing Letters | Ausgabe 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.
Vorheriger Artikel Two-Stage Method for Diagonal Recurrent Neural Network Identification of a High-Power Continuous Microwave Heating System
Nächster Artikel Impulsive Stabilization and Synchronization of Fractional-Order Complex-Valued Neural Networks

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Metadaten
Titel
Global Exponential Synchronization of Delayed Complex-Valued Recurrent Neural Networks with Discontinuous Activations
verfasst von
Lian Duan
Min Shi
Zengyun Wang
Lihong Huang
Publikationsdatum
15.02.2019
Verlag
Springer US
Erschienen in
Neural Processing Letters / Ausgabe 3/2019
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI
https://doi.org/10.1007/s11063-018-09970-8

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