Non-fragile robust synchronization for Markovian jumping chaotic neural networks of neutral-type with randomly occurring uncertainties and mode-dependent time-varying delays

- Robust synchronization scheme for Markovian jumping chaotic neural networks are studied.
- Randomly occurring uncertainties and randomly occurring control gain fluctuations are used for the non-fragile control scheme.
- Combined-convex techniques are used to derive the main results.
- This network involves both mode dependent discrete and mode dependent distributed time varying delays.
- The results are derived in terms of LMIs.

This paper deals with the problem of robust synchronization for uncertain chaotic neutral-type Markovian jumping neural networks with randomly occurring uncertainties and randomly occurring control gain fluctuations. Then, a sufficient condition is proposed for the existence of non-fragile output controller in terms of linear matrix inequalities (LMIs). Uncertainty terms are separately taken into consideration. This network involves both mode dependent discrete and mode dependent distributed time-varying delays. Based on the Lyapunov-Krasovskii functional (LKF) with new triple integral terms, convex combination technique and free-weighting matrices method, delay-dependent sufficient conditions for the solvability of these problems are established in terms of LMIs. Furthermore, the problem of non-fragile robust synchronization is reduced to the optimization problem involving LMIs, and the detailed algorithm for solving the restricted LMIs is given. Numerical examples are provided to show the effectiveness of the proposed theoretical results.