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The reservoir computing (RC) is increasingly used to learn the synchronization behavior of chaotic systems as well as the dynamical behavior of complex systems, but it is scarcely applied in studying synchronization of non-smooth chaotic systems likely due to its complexity leading to the unimpressive effect. Here proposes a simulated annealing-based differential evolution (SADE) algorithm for the optimal parameter selection in the reservoir, and constructs an improved RC model for synchronization, which can work well not only for non-smooth chaotic systems but for smooth ones. Extensive simulations show that the trained RC model with optimal parameters has far longer prediction time than those with empirical and random parameters. More importantly, the well-trained RC system can be well synchronized to its original chaotic system as well as its replicate RC system via one shared signal, whereas the traditional RC system with empirical or random parameters fails for some chaotic systems, particularly for some non-smooth chaotic systems. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of stochastic delayed multilayer networks with additive couplings. Multilayer networks are a kind of complex networks with different layers, which consist of different kinds of interactions or multiple subnetworks. Additive couplings are designed to capture the different layered connections. Based on additive couplings, several sufficient conditions are obtained to guarantee the synchronization of chaotic stochastic delayed coupled multilayer network. More specifically, on one hand, we obtain some sufficient conditions to guarantee that the stochastic multilayer network can be synchronized almost surely without control input. On the other hand, we propose three synchronization schemes by designing controllers. Scheme I: It is assumed that only a part of the nodes are allowed to be controlled directly. Scheme II: Control all nodes of the complex system by using only one controller. Scheme III: Pinning adaptive controller. Finally, an example and its simulations are given to show the effectiveness of our control schemes. [ABSTRACT FROM AUTHOR]