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A guide to neural computing applications /

Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but t...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Tarassenko, Lionel
Autor Corporativo: Neural Computing Applications Forum
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : New York : Arnold ; Co-published in North, Central, and South America by John Wiley, �1998.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Tarassenko, Lionel. 
245 1 2 |a A guide to neural computing applications /  |c Lionel Tarassenko. 
260 |a London :  |b Arnold ;  |a New York :  |b Co-published in North, Central, and South America by John Wiley,  |c �1998. 
300 |a 1 online resource (x, 139 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a On t.p.: Neural Computing Applications Forum. 
500 |a "Commissioned for [Neural Computing Applications Forum] members"--Page ix 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Front Cover; A Guide to Neural Computing Applications; Copyright Page; Contents; Foreword; Chapter 1. Introduction; Chapter 2. Mathematical background for neural computing; Chapter 3. Managing a neural computing project; Chapter 4. Identifying applications and assessing their feasibility; Chapter 5. Neural computing hardware and software; Chapter 6. Collecting and preparing data; Chapter 7. Design, training and testing of the prototype; Chapter 8. The case studies; Chapter 9. More advanced topics; Appendix A: The error back-propagation algorithm for weight updates in an MLP. 
520 |a Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately. This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more. 
506 |3 Use copy  |f Restrictions unspecified  |2 star  |5 MiAaHDL 
533 |a Electronic reproduction.  |b [Place of publication not identified] :  |c HathiTrust Digital Library,  |d 2011.  |5 MiAaHDL 
538 |a 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.  |u http://purl.oclc.org/DLF/benchrepro0212  |5 MiAaHDL 
583 1 |a digitized  |c 2011  |h HathiTrust Digital Library  |l committed to preserve  |2 pda  |5 MiAaHDL 
546 |a English. 
650 0 |a Neural networks (Computer science) 
650 0 |a Neural computers. 
650 6 |a R�eseaux neuronaux (Informatique)  |0 (CaQQLa)201-0209597 
650 6 |a Ordinateurs neuronaux.  |0 (CaQQLa)201-0191036 
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710 2 |a Neural Computing Applications Forum. 
776 0 8 |i Print version:  |a Tarassenko, Lionel.  |t Guide to neural computing applications.  |d London : Arnold ; New York : Co-published in North, Central, and South America by John Wiley, �1998  |z 0340705892  |z 9780340705896  |w (DLC) 98140310  |w (OCoLC)39182577 
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