MARC Record from marc_columbia

LEADER: 02001mam a2200265 a 4500
001 1739556
005 20220608223706.0
008 960223t19961996enka 001 0 eng d
020 $a1850321701 :$c$52.95
035 $a(OCoLC)ocm34259075
035 $9ALE9652CU
035 $a1739556
040 $aOCO$cOCO$dTAI$dOrLoB-B
100 1 $aBengio, Yoshua.$0http://id.loc.gov/authorities/names/nr96012906
245 10 $aNeural networks for speech and sequence recognition /$cYoshua Bengio.
260 $aLondon ;$aNew York :$bInternational Thomson Computer Press,$c[1996], ©1996.
300 $aviii, 167 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
504 $aIncludes bibliographical references (p.145-152) and index.
505 00 $g1.$tIntroduction --$g2.$tThe Back-Propagation Algorithm --$g3.$tIntegrating Domain Knowledge and Learning from Examples --$g4.$tSequence Analysis --$g5.$tIntegrating ANNs with Other Systems --$g6.$tRadial Basis Functions and Local Representation --$g7.$tDensity Estimation with a Neural Network --$g8.$tPost-Processors Based on Dynamic Programming.
520 $aSequence recognition is a crucial element in many applications in the fields of speech analysis and recognition, time-series prediction, control and signal monitoring. This book applies the techniques of neural networks and hidden Markov models to problems of pattern and speech recognition, using real-world examples throughout.
520 8 $aHighlights include the incorporation of domain knowledge with learning from examples, the description of contemporary advances such as recurrent neural networks, hybrids with hidden Markov models, and a thorough but straightforward use of mathematics. Neural Networks for Speech and Sequence Recognition will prove valuable to researchers and graduate students alike.
650 0 $aNeural networks (Computer science)$0http://id.loc.gov/authorities/subjects/sh90001937
852 00 $boff,eng$hQA76.87$i.B45 1996g