| Record ID | ia:simulatingneural0000free |
| Source | Internet Archive |
| Download MARC XML | https://archive.org/download/simulatingneural0000free/simulatingneural0000free_marc.xml |
| Download MARC binary | https://www.archive.org/download/simulatingneural0000free/simulatingneural0000free_meta.mrc |
LEADER: 03554cam 2200649 a 4500
001 ocm26160830
003 OCoLC
005 20200513235839.0
008 920615s1994 maua b 001 0 eng
010 $a 92002345
040 $aDLC$beng$cDLC$dUBA$dNLGGC$dBTCTA$dYDXCP$dTULIB$dEUM$dGBVCP$dOCLCO$dOCLCF$dOCLCQ$dLIP$dVGM$dOCLCQ$dOCLCO$dDHA$dL2U
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020 $a020156629X
020 $a9780201566291
035 $a(OCoLC)26160830$z(OCoLC)29906353$z(OCoLC)222247362
050 00 $aQA76.87$b.F72 1994
082 00 $a006.3$220
084 $a54.72$2bcl
084 $a006.32
100 1 $aFreeman, James A.
245 10 $aSimulating neural networks with Mathematica /$cJames A. Freeman.
260 $aReading, Mass. :$bAddison-Wesley,$c℗♭1994.
300 $ax, 341 pages :$billustrations ;$c25 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
504 $aIncludes bibliographical references (pages 335-336) and index.
505 0 $a1. Introduction to Neural Networks and Mathematica -- 1.1. The Neural-Network Paradigm -- 1.2. Neural-Network Fundamentals -- 2. Training by Error Minimization -- 2.1. Adaline and the Adaptive Linear Combiner -- 2.2. The LMS Learning Rule -- 2.3. Error Minimization in Multilayer Networks -- 3. Backpropagation and Its Variants -- 3.1. The Generalized Delta Rule -- 3.2. BPN Examples -- 3.3. BPN Variations -- 3.4. The Functional Link Network -- 4. Probability and Neural Networks -- 4.1. The Discrete Hopfield Network -- 4.2. Stochastic Methods for Neural Networks -- 4.3. Bayesian Pattern Classification -- 4.4. The Probabilistic Neural Network -- 5. Optimization and Constraint Satisfaction -- 5.1. The Traveling Salesperson Problem (TSP) -- 5.2. Neural Networks and the TSP -- 6. Feedback and Recurrent Networks -- 6.1. The BAM -- 6.2. Recognition of Time Sequences -- 7. Adaptive Resonance Theory -- 7.1. ART1 -- 7.2. ART2 -- 8. Genetic Algorithms -- 8.1. GA Basics -- 8.2. A Basic Genetic Algorithm (BGA) -- 8.3. A GA for Training Neural Networks -- Appendix A Code Listings.
630 00 $aMathematica (Computer file)
650 0 $aNeural networks (Computer science)
630 04 $aMathematica (Computer file)
650 7 $a54.72 artificial intelligence.$0(NL-LeOCL)077605411$2bcl
630 07 $aMathematica (Computer file)$2fast$0(OCoLC)fst01372712
650 7 $aNeural networks (Computer science)$2fast$0(OCoLC)fst01036260
650 17 $aKunstmatige intelligentie.$2gtt
650 17 $aNeurale netwerken.$2gtt
650 17 $aMathematica (computerprogramma)$2gtt
650 7 $aInteligencia artificial (computacao)$2larpcal
653 0 $aMathematica (Computer file)
653 0 $aNeural networks (Computer science)
776 08 $iOnline version:$aFreeman, James A.$tSimulating neural networks with Mathematica.$dReading, Mass. : Addison-Wesley, ℗♭1994$w(OCoLC)622500014
856 41 $3Table of contents$uhttp://www.gbv.de/dms/bowker/toc/9780201566291.pdf
938 $aBaker and Taylor$bBTCP$n92002345 //r93
938 $aYBP Library Services$bYANK$n122914
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948 $hNO HOLDINGS IN P4A - 290 OTHER HOLDINGS