Replication Of Chaos In Neural Networks, Economics And Physics (nonlinear Physical Science)
by Marat Akhmet /
2015 / English / PDF
32.3 MB Download
This 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.
This 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.