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Globally exponential synchronization in an array of asymmetric coupled neural networks. (English) Zbl 1209.37108
Summary: We study the globally exponential synchronization in an array of linearly coupled neural networks with delayed coupling. The coupling configuration matrix is assumed to be asymmetric, which is more coincident with the real-world network. The difficulty arising from the asymmetry of the coupling matrix has been overcame in this work. Some synchronization criteria are given in terms of strict linear matrix inequalities (LMIs), which can be efficiently solved by using interior point algorithm. Some previous synchronization results are generalized. Numerical simulation is also given to verify our theoretical analysis.

MSC:
37N25Dynamical systems in biology
34K20Stability theory of functional-differential equations
37N35Dynamical systems in control
92B20General theory of neural networks (mathematical biology)
93D20Asymptotic stability of control systems