This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.
Neural networks are important tools for solving problems in many fields of applied sciences. ... The volume is equipped with many figures, numerical examples and numerical simulations. Moreover, each chapter contains several references. The book can be recommended to readers having good knowledge in the foundations of neural networks, dynamical control systems and stochastic analysis. (Kurt Marti, zbMATH 1355.60007, 2017)