An Introduction to Neural Network Methods for Differential Equations

Anupam Yadav, Neha Yadav, Manoj Kumar, et al.

PDF
ca. 74,89
Amazon iTunes Thalia.de Weltbild.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Springer Netherland img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Sonstiges

Beschreibung

This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications.

The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field.

Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.

Weitere Titel in dieser Kategorie
Cover Mathematics in Politics and Governance
Francisco J. Aragón-Artacho
Cover The Blue Book
Stamatina Th. Rassia
Cover Virtual Barrels
Ilia Bouchouev

Kundenbewertungen

Schlagwörter

ordinary differential equations, Mathematical Model of Neural Network, Cellular Neural Network, Learning in Neural Networks, Neural Network Architecture, Wavelet Neural Network, History of Neural Networks, Multilayer Perceptron, Radial Basis Functions, Finite Element Neural Network, Neural network methods for differential equations