Conclusions

In recent years, the researches on the synchronization of complex neural networks have achieved important results, which could better understand and explain the various dynamical phenomena in the real world. The dynamical behaviour of complex neural networks is of great importance for the development of society and the economy. This monograph mainly studies the stochastic synchronization, local synchronization, and sampled-data synchronization of Markovian complex neural network with time-varying delays. Based on different Lyapunov–Krasovskii functional, integral inequality and generally Markovian jumping, the corresponding synchronization criteria are proposed, respectively.