Stability and synchronization analysis of inertial memristive neural networks with time delays.
This paper is concerned with the problem of stability and pinning synchronization of a class of inertial memristive neural networks with time delay. In contrast to general inertial neural networks, inertial memristive neural networks is applied to exhibit the synchronization and stability behaviors due to the physical properties of memristors and the differential inclusion theory. By choosing an appropriate variable transmission, the original system can be transformed into first order differential equations. Then, several sufficient conditions for the stability of inertial memristive neural networks by using matrix measure and Halanay inequality are derived. These obtained criteria are capable of reducing computational burden in the theoretical part. In addition, the evaluation is done on pinning synchronization for an array of linearly coupled inertial memristive neural networks, to derive the condition using matrix measure strategy. Finally, the two numerical simulations are presented to show the effectiveness of acquired theoretical results.
Department of Mathematics, Bharathiar University, Coimbatore, Tamil Nadu 641 046 India.
R
R
Rakkiyappan
Department of Mathematics, Bharathiar University, Coimbatore, Tamil Nadu 641 046 India.
S
S
Premalatha
Department of Mathematics, Bharathiar University, Coimbatore, Tamil Nadu 641 046 India.
A
A
Chandrasekar
Department of Mathematics, Southeast University, Nanjing, 210096 China ; Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, 21589 Saudi Arabia.
Jinde
0000-0003-3133-7119
J
Cao
Halanay inequality; Inertial memristive neural networks; Matrix measure; Pinning control; Synchronization
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