This textbook provides a broad introduction to continuous and discrete dynamical systems. With
its hands-on approach the text leads the reader from basic theory to recently published
research material in nonlinear ordinary differential equations nonlinear optics multifractals
neural networks and binary oscillator computing. Dynamical Systems with Applications Using
Python takes advantage of Python¿s extensive visualization simulation and algorithmic tools
to study those topics in nonlinear dynamical systems through numerical algorithms and generated
diagrams.After a tutorial introduction to Python the first part of the book deals with
continuous systems using differential equations including both ordinary and delay differential
equations. The second part of the book deals with discrete dynamical systems and progresses to
the study of both continuous and discrete systems in contexts like chaos control and
synchronization neural networks and binary oscillator computing. These later sections are
useful reference material for undergraduate student projects. The book is rounded off with
example coursework to challenge students¿ programming abilities and Python-based exam
questions. This book will appeal to advanced undergraduate and graduate students applied
mathematicians engineers and researchers in a range of disciplines such as biology
chemistry computing economics and physics. Since it provides a survey of dynamical systems
a familiarity with linear algebra real and complex analysis calculus and ordinary
differential equations is necessary and knowledge of a programming language like C or Java is
beneficial but not essential.
