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020 _a9780470694077
020 _a0470694076
020 _a1405143894
020 _a9781405143899
020 _a9781405130745
_q(hardcover ;
_qalk. paper)
020 _a1405130741
_q(hardcover ;
_qalk. paper)
020 _a9781405128070
_q(pbk. ;
_qalk. paper)
020 _a1405128070
_q(pbk. ;
_qalk. paper)
020 _z1405130741
020 _z1405128070
024 7 _a10.1002/9780470694077
_2doi
029 1 _aAU@
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029 1 _aDEBBG
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029 1 _aDEBSZ
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035 _a(OCoLC)214281471
_z(OCoLC)61363629
_z(OCoLC)225111250
_z(OCoLC)299697310
_z(OCoLC)505096983
_z(OCoLC)646757912
035 _a(OCoLC)ocn214281471
037 _a10.1002/9780470694077
_bWiley InterScience
_nhttp://www3.interscience.wiley.com
039 9 _a201904261151
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082 0 4 _a153
_222
090 _aebook
100 1 _aDawson, Michael Robert William,
_d1959-
245 1 0 _aConnectionism :
_ba hands-on approach /
_cMichael R.W. Dawson.
250 _a1st ed.
260 _aOxford, UK ;
_aMalden, MA :
_bBlackwell Pub.,
_c2005.
300 _a1 online resource (viii, 200 pages) :
_billustrations
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references (pages 188-194) and indexes.
505 0 _aCh. 1. Hands-on connectionism -- Ch. 2. The distributed associative memory -- Ch. 3. The James program -- Ch. 4. Introducing Hebb learning -- Ch. 5. Limitations of Hebb learning -- Ch. 6. Introducing the delta rule -- Ch. 7. Distributed networks and human memory -- Ch. 8. Limitations of delta rule learning -- Ch. 9. The perceptron -- Ch. 10. The Rosenblatt program -- Ch. 11. Perceptrons and logic gates -- Ch. 12. Performing more logic with perceptrons -- Ch. 13. Value units and linear nonseparability -- Ch. 14. Network by problem type interactions -- Ch. 15. Perceptrons and generalization -- Ch. 16. Animal learning theory and perceptrons -- Ch. 17. The multilayer perceptron -- Ch. 18. The Rumelhart program -- Ch. 19. Beyond the perceptron's limits -- Ch. 20. Symmetry as a second case study -- Ch. 21. How many hidden units? -- Ch. 22. Scaling up with the parity problem -- Ch. 23. Selectionism and parity -- Ch. 24. Interpreting a small network.
505 8 _aCh. 25. Interpreting networks of value units -- Ch. 26. Interpreting distributed representations -- Ch. 27. Creating your own training sets.
520 _aCONNNECTIONISM is a'hands on' introduction to connectionist modeling. Three different types of connectionist architectures - distributed associative memory, perceptron, and multilayer perceptron - are explored. In an accessible style, Dawson provides a brief overview of each architecture, a detailed introduction on how to use a program to explore this network, and a series of practical exercises that are designed to highlight the advantages, and disadvantages, of each and to provide a'road map' to the field of cognitive modeling. This book is designed to be used as a stand-alone volume, or a.
588 0 _aPrint version record.
650 0 _aConnectionism.
650 7 _aPSYCHOLOGY
_xCognitive Psychology.
_2bisacsh
650 7 _aSCIENCE
_xCognitive Science.
_2bisacsh
650 7 _aConnectionism.
_2fast
_0(OCoLC)fst00875336
650 1 7 _aConnectionisme.
_2gtt
650 1 7 _aCognitieve processen.
_2gtt
655 4 _aElectronic books.
710 2 _aWiley InterScience (Online service)
773 0 _tWiley e-books.
776 0 8 _iPrint version:
_aDawson, Michael Robert William, 1959-
_tConnectionism.
_b1st ed.
_dOxford, UK ; Malden, MA : Blackwell Pub., 2005
_z1405130741
_z9781405130745
_w(DLC) 2004028929
_w(OCoLC)57193241
856 4 0 _uhttp://www.ezplib.ukm.edu.my/login?url=http://onlinelibrary.wiley.com/book/10.1002/9780470694077
_zWiley Online Library
907 _a.b16537518
_b2021-06-25
_c2019-11-12
942 _c01
_n0
_kebook
914 _avtls003628673
998 _ae
_b2017-08-12
_cm
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_z.b16537518
999 _c690218
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