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003    OCoLC 
005    20160527041014.9 
006    m     o  d         
007    cr cn||||||||| 
008    980211s1999    maua    ob    001 0 eng d 
019    47920213|a60690085|a437427115|a508274322|a532440766
       |a606014358 
020    0585078386|q(electronic book) 
020    9780585078380|q(electronic book) 
020    9780262282215|q(electronic book) 
020    0262282216|q(electronic book) 
020    |z0262181908|q(hc ;|qalkaline paper) 
020    |z9780262181907|q(hc ;|qalkaline paper) 
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       |z(OCoLC)437427115|z(OCoLC)508274322|z(OCoLC)532440766
       |z(OCoLC)606014358 
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049    RIDW 
050  4 QA76.87|b.R44 1998eb 
072  7 COM|x000000|2bisacsh 
082 04 006.3/2|221 
090    QA76.87|b.R44 1998eb 
100 1  Reed, Russell D.|0https://id.loc.gov/authorities/names/
       n98013993 
245 10 Neural smithing :|bsupervised learning in feedforward 
       artificial neural networks /|cRussell D. Reed and Robert 
       J. Marks II. 
264  1 Cambridge, Mass. :|bMIT Press,|c[1999] 
264  4 |c©1999 
300    1 online resource (viii, 346 pages) :|billustrations 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc 
347    text file|2rdaft 
500    "A Bradford book." 
504    Includes bibliographical references (pages 319-338) and 
       index. 
505 00 |g1.|tIntroduction --|g2.|tSupervised learning --|g3.
       |tSingle-layer networks --|g4.|tMLP representational 
       capabilities --|g5.|tBack-propagation --|g6.|tLearning 
       rate and momentum --|g7.|tWeight-initialization techniques
       --|g8.|tError surface --|g9.|tFaster variations of back-
       propagation --|g10.|tClassical optimization techniques --
       |g11.|tGenetic algorithms and neural networks --|g12.
       |tConstructive methods --|g13.|tPruning algorithms --|g14.
       |tFactors influencing generalization --|g15.
       |tGeneralization prediction and assessment --|g16.
       |tHeuristics for improving generalization --|g17.|tEffects
       of training with noisy inputs. 
520 1  "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. 
588 0  Print version record. 
590    eBooks on EBSCOhost|bEBSCO eBook Subscription Academic 
       Collection - North America 
650  0 Neural networks (Computer science)|0https://id.loc.gov/
       authorities/subjects/sh90001937 
650  7 Neural networks (Computer science)|2fast|0https://
       id.worldcat.org/fast/1036260 
655  4 Electronic books. 
700 1  Marks, Robert J.,|cII|q(Robert Jackson),|d1950-|0https://
       id.loc.gov/authorities/names/n91022335 
776 08 |iPrint version:|aReed, Russell D.|tNeural smithing.
       |dCambridge, Mass. : MIT Press, ©1999|z0262181908|w(DLC)  
       98013416|w(OCoLC)38468402 
830  0 Bradford book.|0https://id.loc.gov/authorities/names/
       n83745008 
856 40 |uhttps://rider.idm.oclc.org/login?url=http://
       search.ebscohost.com/login.aspx?direct=true&scope=site&
       db=nlebk&AN=9366|zOnline eBook. Access restricted to 
       current Rider University students, faculty, and staff. 
856 42 |3Instructions for reading/downloading this eBook|uhttp://
       guides.rider.edu/ebooks/ebsco 
901    MARCIVE 20231220 
948    |d20160615|cEBSCO|tebscoebooksacademic|lridw 
994    92|bRID