Numerical Solutions Using Cellular by Eissa Mahmoud (6 results)

Paperback. Condition: Brand New. 160 pages. 8.66x5.91x0.37 inches. In Stock.

Taschenbuch. Condition: Neu. Numerical Solutions Using Cellular Neural Networks | How to Use Cellular Neural Networks to Approximate Ordinary and Partial Differential Equations? | Mahmoud A. Eissa (u. a.) | Taschenbuch | 160 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659976308 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 160 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Eissa Mahmoud A.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, Differe.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 160 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.