1# Library to Find Best eBook for Read
Author : Jia-Bao Liu
Release : 2021-12-03
Genre : Science
Kind : eBook
Book Rating : 976/5 ( reviews)
Book Synopsis Mathematical Treatment of Nanomaterials and Neural Networks by : Jia-Bao Liu
Download or read book Mathematical Treatment of Nanomaterials and Neural Networks written by Jia-Bao Liu. This book was released on 2021-12-03. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Martin Anthony
Release : 2001-01-01
Genre : Computers
Kind : eBook
Book Rating : 80X/5 ( reviews)
Book Synopsis Discrete Mathematics of Neural Networks by : Martin Anthony
Download or read book Discrete Mathematics of Neural Networks written by Martin Anthony. This book was released on 2001-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.
Author : Stephen W. Ellacott
Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 993/5 ( reviews)
Book Synopsis Mathematics of Neural Networks by : Stephen W. Ellacott
Download or read book Mathematics of Neural Networks written by Stephen W. Ellacott. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: This volume of research papers comprises the proceedings of the first International Conference on Mathematics of Neural Networks and Applications (MANNA), which was held at Lady Margaret Hall, Oxford from July 3rd to 7th, 1995 and attended by 116 people. The meeting was strongly supported and, in addition to a stimulating academic programme, it featured a delightful venue, excellent food and accommo dation, a full social programme and fine weather - all of which made for a very enjoyable week. This was the first meeting with this title and it was run under the auspices of the Universities of Huddersfield and Brighton, with sponsorship from the US Air Force (European Office of Aerospace Research and Development) and the London Math ematical Society. This enabled a very interesting and wide-ranging conference pro gramme to be offered. We sincerely thank all these organisations, USAF-EOARD, LMS, and Universities of Huddersfield and Brighton for their invaluable support. The conference organisers were John Mason (Huddersfield) and Steve Ellacott (Brighton), supported by a programme committee consisting of Nigel Allinson (UMIST), Norman Biggs (London School of Economics), Chris Bishop (Aston), David Lowe (Aston), Patrick Parks (Oxford), John Taylor (King's College, Lon don) and Kevin Warwick (Reading). The local organiser from Huddersfield was Ros Hawkins, who took responsibility for much of the administration with great efficiency and energy. The Lady Margaret Hall organisation was led by their bursar, Jeanette Griffiths, who ensured that the week was very smoothly run.
Author : Neha Yadav
Release : 2015-02-26
Genre : Mathematics
Kind : eBook
Book Rating : 168/5 ( reviews)
Book Synopsis An Introduction to Neural Network Methods for Differential Equations by : Neha Yadav
Download or read book An Introduction to Neural Network Methods for Differential Equations written by Neha Yadav. This book was released on 2015-02-26. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : J.G. Taylor
Release : 1993-10-27
Genre : Computers
Kind : eBook
Book Rating : 392/5 ( reviews)
Book Synopsis Mathematical Approaches to Neural Networks by : J.G. Taylor
Download or read book Mathematical Approaches to Neural Networks written by J.G. Taylor. This book was released on 1993-10-27. Available in PDF, EPUB and Kindle. Book excerpt: The subject of Neural Networks is being seen to be coming of age, after its initial inception 50 years ago in the seminal work of McCulloch and Pitts. It is proving to be valuable in a wide range of academic disciplines and in important applications in industrial and business tasks. The progress being made in each approach is considerable. Nevertheless, both stand in need of a theoretical framework of explanation to underpin their usage and to allow the progress being made to be put on a firmer footing.This book aims to strengthen the foundations in its presentation of mathematical approaches to neural networks. It is through these that a suitable explanatory framework is expected to be found. The approaches span a broad range, from single neuron details to numerical analysis, functional analysis and dynamical systems theory. Each of these avenues provides its own insights into the way neural networks can be understood, both for artificial ones and simplified simulations. As a whole, the publication underlines the importance of the ever-deepening mathematical understanding of neural networks.
