Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 30, Issue 3, Pages 951-958Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2018.2853650
Keywords
Control; Markov; proportional delay; quantization; synchronization
Categories
Funding
- National Natural Science Foundation of China [61673078, 61573102, 61773155]
- Chongqing Normal University through the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence [BM2017002]
- Natural Science Foundation of Henan Province of China [172102210212]
- Chongqing Natural Science Foundation [cstc2018jcyjAX0369]
Ask authors/readers for more resources
The asymptotic synchronization of coupled reaction-diffusion neural networks with proportional delay and Markovian switching topologies is considered in this brief where the diffusion space does not need to contain the origin. The main objectives of this brief are to save communication resources and to reduce the conservativeness of the obtained synchronization criteria, which are carried out from the following two aspects: 1) mode-dependent quantized control technique is designed to reduce control cost and save communication channels and 2) Wirtinger inequality is utilized to deal with the reaction-diffusion terms in a matrix form and reciprocally convex technique combined with new Lyapunov-Krasovskii functional is used to derive delay-dependent synchronization criteria. The obtained results are general and formulated by linear matrix inequalities. Moreover, combined with an optimal algorithm, control gains with the least magnitude are designed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available