Synchronization of discrete-time neural networks with time delays subject to missing data

• This paper is concerned with the problem of synchronization of discrete-time neural networks with time-delays under unreliable communication links.
• Some delay-dependent synchronization criteria are obtained and formulated in the form of linear matrix inequalities.
• A feedback controller has been designed such that the master system and the slave system are globally exponentially synchronized in the mean square.

This paper is concerned with the problem of synchronization of discrete-time neural networks with time-delays under unreliable communication links, which are modeled as stochastic dropouts. The process of missing data satisfies a discrete-time Markov chain with two state components. By using Lyapunov functional approach, some delay-dependent synchronization criteria are first obtained and formulated in the form of linear matrix inequalities (LMIs). Then, sufficient conditions on the existence of feedback controllers are derived by employing these newly obtained synchronization criteria. The controller gains can be achieved by solving a set of LMIs. Finally, a numerical example is given to illustrate the effectiveness of the design method.