Akhmet M., Fen M.O. Replication of Chaos in Neural Networks, Economics and Physics

Higher Education Press, Beijing and Springer-Verlag, Berlin, Heidelberg, 2016. – 457 p. – ISBN: 3662474999This book presents detailed descriptions of chaos for continuous-time systems. It is the first-ever book to consider chaos as an input for differential and hybrid equations. Chaotic sets and chaotic functions are used as inputs for systems with attractors: equilibrium points, cycles and tori. The findings strongly suggest that chaos theory can proceed from the theory of differential equations to a higher level than previously thought. The approach selected is conducive to the in-depth analysis of different types of chaos. The appearance of deterministic chaos in neural networks, economics and mechanical systems is discussed theoretically and supported by simulations. As such, the book offers a valuable resource for mathematicians, physicists, engineers and economists studying nonlinear chaotic dynamics.Replication of Continuous Chaos About Equilibria
Chaos Extension in Hyperbolic Systems
Entrainment by Chaos
Chaotification of Impulsive Systems
Chaos Generation in Continuous/Discrete-Time Models
Economic Models with Exogenous Continuous/Discrete Shocks
Chaos by Neural Networks
The Prevalence of Weather Unpredictability