Global Synchronization in Arrays of Coupled Neural Networks with Uncertainties and Mixed Delays
N. Yotha1, A. Klamnoi2, T. Botmart3
1N. Yotha, Department of Applied Mathematics and Statistics, Rajamangala University of Technology Isan, Nakhon Ratchasima, Thailand.
2A. Klamnoi, Department of Applied Mathematics and Statistics, Rajamangala University of Technology Isan, Nakhon Ratchasima, Thailand.
3T. Botmart, Department of Mathematics, Khon Kaen University, Khon Kaen Thailand.
Manuscript received on 15 December 2018 | Revised Manuscript received on 27 December 2018 | Manuscript Published on 24 January 2019 | PP: 294-298 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: ES20114017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper deal with the problem of global synchronization in arrays of coupled neural networks with uncertainties and mixed delays. By construction of a suitable Lyapunov-Krasovskii’s functional (LKF), Kronecker product properties and utilization of Wirtinger’s inequality, novel delay-dependent criteria for the robust synchronization of the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. A numerical example is given to illustrate the effectiveness of the proposed method.
Keywords: Synchronization, Neural Networks, Time-Varying Delay, Leakage Delay.
Scope of the Article: Embedded Networks