Premium
Uniform Quantized Synchronization for Chaotic Neural Networks with Successive Packet Dropouts
Author(s) -
Niu Yichun,
Sheng Li
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1736
Subject(s) - synchronization (alternating current) , artificial neural network , network packet , chaotic , control theory (sociology) , computer science , chaotic systems , bounded function , mathematics , artificial intelligence , mathematical analysis , computer network , control (management) , channel (broadcasting)
In this paper, the problem of uniform quantized synchronization is investigated for chaotic neural networks with packet dropouts. By means of the stochastic analysis approach and inequality technique, sufficient conditions are derived under which the synchronization error system is exponentially ultimately bounded in mean square. Finally, a numerical example is provided to validate the feasibility and effectiveness of the proposed results.