Non-fragile synchronization of neural networks with time-varying delay and randomly occurring controller gain fluctuation

In this paper, a non-fragile procedure is introduced to study the problem of synchronization of neural networks with time-varying delay. The controller gain fluctuation appears in a random way, which obeys certain Bernoulli distributed white noise sequences. Based on the linear matrix inequality (LMI) method, two delay-dependent criteria are derived to ensure the exponential stability of the error systems, which implies the master systems synchronize with the slave systems. The non-fragile controller can be obtained by solving a set of LMIs. A simulation example is given to illustrate the effectiveness of the proposed method.