Modelling with ordinary differential equations : a comprehensive approach
著者
書誌事項
Modelling with ordinary differential equations : a comprehensive approach
（Chapman & Hall/CRC numerical analysis and scientific computing）
Chapman & Hall/CRC, 2020
- hbk.
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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
目次
1. Introduction. 2. Elementary solution methods for simple ODEs. 3. Theory of ordinary differential equations. 4. Systems of ordinary differentail equations. 5. Ordinary differential equations of order n. 6. Stability of ODE systems. 7. Boundary and eigenvalue problems. 8. Numerical solution of ODE problems. 9. ODEs and the calculus of variations. 10. Optimal control of ODE models. 11. Inverse problems with ODE models. 12. Differential games. 13. Stochastic differential equations. 14. Neural networks and ODE problems.
「Nielsen BookData」 より
