Numerical Solutions Using Cellular Neural Networks: How to Use Cellular Neural Networks to Approximate Ordinary and Partial Differential Equations?

Eissa, Mahmoud A./ Eldanaf, Talaat S./ Ramadan, Mohamed A.

ISBN 10: 365997630X / ISBN 13: 9783659976308

Published by LAP LAMBERT Academic Publishing, 2016

About this Item

160 pages. 8.66x5.91x0.37 inches. In Stock.

Seller Inventory # 365997630X

Bibliographic Details

• Title: Numerical Solutions Using Cellular Neural Networks: How to Use Cellular Neural Networks to Approximate Ordinary and Partial Differential Equations?
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2016
• Language: English
• ISBN 10: 365997630X
• ISBN 13: 9783659976308
• Binding: Paperback
• Condition: Brand New
• Weight: 0.29 kilograms

About this title

Synopsis

The presentation of the book is designed to be suitable for senior level undergraduate or beginning level graduate students in mathematics, computer science, physical science and engineering. This book helps the reader gain a fundamental introduction to using cellular neural networks to approximate some types of ordinary and partial differential equations. After overview of basic concepts of the matrix algebra, cellular neural networks, ordinary differential equations, and partial differential equations, the deeper background about the cellular neural networks are provided with a general introduction of cellular neural networks models. The basic steps for using cellular neural network models to solve some types of linear and non-linear systems of ordinary and partial differential equations are presented. Furthermore, the performance of the cellular neural networks models are illustrated by solving different types of test equations. The stability properties are discussed. A brief introduction for MATLAB and SIMULINK are presented to be the reader should be able to create and modify programs based on the algorithms in this book.

About the Author

Mahmoud A. Eissa is Assistant Lecturer at Menoufia University, Egypt. Phd candidate at Harbin Institute of Technology, China. Eissa's research interest in Numerical Analysis methods, Computational Mathematics, Differential equations, Stochastic differential equations, Financial Mathematics, Cellular Neural Networks. Eissa likes to play chess.