ABSTRACT

Modelling with Ordinary Differential Equations: A Comprehensive Approach aims to provide a broad and self-contained introduction to the mathematical tools necessary to investigate and apply ODE models. The book starts by establishing the existence of solutions in various settings and analysing their stability properties. The next step is to illustrate modelling issues arising in the calculus of variation and optimal control theory that are of interest in many applications. This discussion is continued with an introduction to inverse problems governed by ODE models and to differential games.

The book is completed with an illustration of stochastic differential equations and the development of neural networks to solve ODE systems. Many numerical methods are presented to solve the classes of problems discussed in this book.

Features:

  • Provides insight into rigorous mathematical issues concerning various topics, while discussing many different models of interest in different disciplines (biology, chemistry, economics, medicine, physics, social sciences, etc.)
  • Suitable for undergraduate and graduate students and as an introduction for researchers in engineering and the sciences
  • Accompanied by codes which allow the reader to apply the numerical methods discussed in this book in those cases where analytical solutions are not available

chapter Chapter 1|11 pages

Introduction

chapter Chapter 2|11 pages

Elementary solution methods for simple ODEs

chapter Chapter 3|14 pages

Theory of ordinary differential equations

chapter Chapter 4|37 pages

Systems of ordinary differential equations

chapter Chapter 5|12 pages

Ordinary differential equations of order n

chapter Chapter 6|50 pages

Stability of ODE systems

chapter Chapter 7|9 pages

Boundary and eigenvalue problems

chapter Chapter 8|40 pages

Numerical solution of ODE problems

chapter Chapter 9|36 pages

ODEs and the calculus of variations

chapter Chapter 10|49 pages

Optimal control of ODE models

chapter Chapter 11|13 pages

Inverse problems with ODE models

chapter Chapter 12|19 pages

Differential games

chapter Chapter 13|22 pages

Stochastic differential equations

chapter Chapter 14|25 pages

Neural networks and ODE problems