MARC Record from marc_columbia

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001 4248407
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006 m o d
007 cr cn|||||||||
008 001009s1998 maua ob 001 0 eng d
035 $a(OCoLC)ocm45731854
035 $a(NNC)4248407
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020 $a0585280010$q(electronic bk.)
020 $a9780585280011$q(electronic bk.)
020 $z0792381580$q(alk. paper)
020 $z9780792381587
024 7 $a10.1007/b102308$2doi
035 $a(OCoLC)45731854$z(OCoLC)55045951$z(OCoLC)66742888$z(OCoLC)556277307$z(OCoLC)647658991$z(OCoLC)818956770$z(OCoLC)961654613$z(OCoLC)962710547$z(OCoLC)984876220$z(OCoLC)1035711664$z(OCoLC)1053025017$z(OCoLC)1078864990$z(OCoLC)1259154741
050 4 $aQA76.87$b.N4955 1998eb
072 7 $aTEC$x009070$2bisacsh
072 7 $aTJFC$2bicssc
082 04 $a621.39/5$221
049 $aZCUA
245 00 $aNeuromorphic systems engineering :$bneural networks in silicon /$cedited by Tor Sverre Lande.
260 $aBoston :$bKluwer Academic,$c©1998.
300 $a1 online resource (xvi, 462 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aKluwer international series in engineering and computer science. Analog circuits and signal processing ;$vSECS 447
504 $aIncludes bibliographical references and index.
520 $aNeuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses /LIST Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
588 0 $aPrint version record.
505 0 $aPart I. Cochlear Systems -- 1. Filter cascades as analogs of the cochlea -- 2. An analogue VLSI model of active cochlea -- 3. A low-power wide-dynamic-range analog VLSI cochlea -- 4. Speech recognition experiments with silicon auditory models -- Part II. Retinomorphic Systems -- 5. The retinomorphic approach: pixel-parallel adaptive amplification, filtering, and quantization -- 6. Analog VLSI excitatory feedback circuits for attentional shifts and tracking -- 7. Floating-gate circuits for adaptation of saccadic eye movement accuracy -- Part III. Neuromorphic Communication -- 8. Introcuction to neuromorphic communication -- 9. A pulsed communication/computation framework for analog VLSI perceptive systems -- 10. Asynchronous communication of 2D motion information using winner-takes-all arbitration -- 11. Communicating neuronal ensembles between neuromorphic chips -- 12. Introduction: from neurobiology to silicon -- 13. A low-power wide-linear-range transconductance amplifier -- 14. Floating-gate MOS synapse transistory -- 15. Neuromorphic synapses for artificial dendrites -- 16. Winner-take-all with lateral networks excitation -- Part V. Neuromorphic Learning -- 17. Neuromorphic learning VLSI systems: a survey -- 18. Analog VLSI stochastic perturbative learning architectures -- 19. Winner-takes-all associative memory: hamming distance vector quantizer.
546 $aEnglish.
650 0 $aNeural networks (Computer science)
650 0 $aIntegrated circuits$xDesign and construction.
650 6 $aRéseaux neuronaux (Informatique)
650 6 $aCircuits intégrés$xConception et construction.
650 7 $aTECHNOLOGY & ENGINEERING$xMechanical.$2bisacsh
650 7 $aIntegrated circuits$xDesign and construction.$2fast$0(OCoLC)fst00975545
650 7 $aNeural networks (Computer science)$2fast$0(OCoLC)fst01036260
653 00 $aengineering
653 00 $acircuits
653 00 $acomputerwetenschappen
653 00 $acomputer sciences
653 00 $acomputertechnieken
653 00 $acomputer techniques
653 00 $aelektrotechniek
653 00 $aelectrical engineering
653 10 $aEngineering (General)
653 10 $aTechniek (algemeen)
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aLande, Tor Sverre,$d1950-
776 08 $iPrint version:$tNeuromorphic systems engineering.$dBoston : Kluwer Academic, ©1998$z0792381580$w(DLC) 98016660$w(OCoLC)38739034
830 0 $aKluwer international series in engineering and computer science.$pAnalog circuits and signal processing ;$vSECS 447.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio4248407$zAll EBSCO eBooks
852 8 $blweb$hEBOOKS