Neural smithing supervised learning in feedforward artificial neural networks (eBook, 1999) [WorldCat.org]
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Neural smithing supervised learning in feedforward artificial neural networks
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Neural smithing supervised learning in feedforward artificial neural networks

Author: Russell D Reed; Robert J Marks
Publisher: 1999
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptions (MLP).  Read more...
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Details

Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Russell D Reed; Robert J Marks
ISBN: 0585078386 9780585078380 9780262282215 0262282216 0262527014 9780262527019
OCLC Number: 1227498094
Notes: "A Bradford book.". - OCLC-licensed vendor bibliographic record.
Description: 1 online resource (viii, 346 pages) illustrations
Responsibility: Russell D. Reed and Robert J. Marks II.

Abstract:

"Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptions (MLP). These are the most widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition)." "This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research."--Jacket.

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