Dynamical Systems with Applications using Python

This resource explores continuous and discrete dynamical systems, providing insights into various applications and numerical methods, making Dynamical Systems with Applications Using Python a valuable tool for students and researchers.

This textbook offers a comprehensive introduction to both continuous and discrete dynamical systems. The hands-on approach guides readers from foundational theories to the latest research in areas such as nonlinear ordinary differential equations, nonlinear optics, multifractals, neural networks, and binary oscillator computing. Dynamical Systems with Applications Using Python leverages Python's powerful visualization, simulation, and algorithmic capabilities to explore these topics through numerical algorithms and generated diagrams.

The book begins with a tutorial on Python, followed by an examination of continuous systems based on differential equations, which includes ordinary and delay differential equations. The second part transitions to discrete dynamical systems and covers the interplay between continuous and discrete systems in contexts like chaos control, synchronization, neural networks, and binary oscillator computing. These later sections serve as valuable reference material for undergraduate student projects, enriching their understanding and application of the concepts.

To further enhance learning, the book concludes with example coursework designed to challenge students' programming skills and includes Python-based exam questions. This resource is ideal for advanced undergraduate and graduate students, applied mathematicians, engineers, and researchers across various disciplines, including biology, chemistry, computing, economics, and physics. While a background in linear algebra, real and complex analysis, calculus, and ordinary differential equations is required, familiarity with programming languages like C or Java is advantageous but not mandatory.