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Aggiungi al carrelloHardcover. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.44.
EUR 37,32
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EUR 27,37
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Aggiungi al carrelloCondizione: New. pp. 360 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
EUR 30,21
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EUR 29,27
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EUR 38,96
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Aggiungi al carrelloCondizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
EUR 44,05
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Da: Turgid Tomes, Nashville, TN, U.S.A.
Prima edizione
EUR 21,07
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Aggiungi al carrellohardcover. Condizione: Good. First Edition. Springer, 1999. Hard cover, first edition. Ex-library copy with the usual markings, otherwise Good condition with no dust jacket, as issued.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 44,89
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Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship toPOboxaddress.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 52,72
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Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship toPOboxaddress.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 58,46
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 60,47
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EUR 53,82
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Da: Best Price, Torrance, CA, U.S.A.
EUR 48,27
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Da: Best Price, Torrance, CA, U.S.A.
EUR 48,27
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EUR 58,55
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network-based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself.
Editore: Springer-Verlag New York Inc., US, 1999
ISBN 10: 0387987452 ISBN 13: 9780387987453
Lingua: Inglese
Da: Rarewaves.com UK, London, Regno Unito
EUR 73,24
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Aggiungi al carrelloHardback. Condizione: New. 1999 ed. The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ?ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network-based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself.
EUR 64,08
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Aggiungi al carrelloGebunden. Condizione: New. This decade has seen an explosive growth in computational speed and memory and a rapid enrichment in our understanding of artificial neural networks. These two factors provide systems engineers and statisticians with the ability to build models of physical,.
EUR 58,45
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EUR 61,24
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 56,93
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Aggiungi al carrelloPF. Condizione: New.
Editore: Springer-Verlag New York Inc., US, 1999
ISBN 10: 0387987452 ISBN 13: 9780387987453
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 79,00
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Aggiungi al carrelloHardback. Condizione: New. 1999 ed. The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ?ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network-based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself.
EUR 66,28
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
EUR 77,30
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Aggiungi al carrelloCondizione: New. pp. 360.
Da: Revaluation Books, Exeter, Regno Unito
EUR 78,75
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Aggiungi al carrelloPaperback. Condizione: Brand New. 356 pages. 9.25x6.10x0.82 inches. In Stock.
Editore: Springer New York Jun 1999, 1999
ISBN 10: 0387987452 ISBN 13: 9780387987453
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 86,02
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Aggiungi al carrelloBuch. Condizione: Neu. Neuware - The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network-based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 52,26
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 52,66
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 107,10
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.