Mathematical approaches to neural networks [electronic resource] / edited by J.G. Taylor.

Contributor(s): Taylor, J. G. (John Gerald), 1931-Material type: Text

TextSeries: North-Holland mathematical library ; v. 51.Publication details: Amsterdam ; New York : North-Holland, 1993. Description: 1 online resource (vii, 382 p.) : illContent type: text Media type: computer Carrier type: online resourceISBN: 9780080887395 (electronic bk.); 0080887392 (electronic bk.); 128179340X; 9781281793409Subject(s): Neural networks (Computer science) -- Mathematics | Neurale netwerken | R�eseaux neuronaux (Informatique) -- Math�ematiques | Neural networks (Computer science) -- Mathematics | COMPUTERS -- Enterprise Applications -- Business Intelligence Tools | COMPUTERS -- Intelligence (AI) & Semantics | Artificial intelligence Mathematical modelsGenre/Form: Electronic books.Additional physical formats: Print version:: Mathematical approaches to neural networks.DDC classification: 006.3 LOC classification: QA76.87 | .M38 1993ebOther classification: 31.80 Online resources: ScienceDirect

Contents:

Front Cover; Mathematical Approaches to Neural Networks, Volume 51; Copyright Page; Preface; Table of Contents; Chapter 1. Control Theory Approach; Chapter 2. Computational Learning Theory for Artificial Neural Networks; Chapter 3. Time-summating Network Approach; Chapter 4. The Numerical Analysis Approach; Chapter 5. Self-organising Neural Networks for Stable Control of Autonomous Behavior in a Changing World; Chapter 6. On-line Learning Processes in Artificial Neural Networks; Chapter 7. Multilayer Functionals; Chapter 8. Neural Networks: The Spin Glass Approach

Action note: digitized 2010 committed to preserveSummary: 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.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 0 )
Title notes ( 9 )
Comments ( 0 )

No physical items for this record

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.

Includes bibliographical references.

Description based on print version record.

Use copy Restrictions unspecified star MiAaHDL

Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL

Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. MiAaHDL

http://purl.oclc.org/DLF/benchrepro0212

digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL

There are no comments on this title.

to post a comment.