9781461375401 - predictive modular neural networks: applications to time series: 466 di petridis, vassilios; kehagias, athanasios (11 risultati)
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 117,13
EUR 14,06 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. In.
Lingua: Inglese
Editore: Springer US, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 92,27
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 148,76
EUR 3,50 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New. pp. 332.
Altre immaginiLingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 95,25
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Predictive Modular Neural Networks | Applications to Time Series | Vassilios Petridis (u. a.) | Taschenbuch | xi | Englisch | 2012 | Springer | EAN 9781461375401 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com |… Anbieter: preigu.
Lingua: Inglese
Editore: Springer, Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 114,36
EUR 62,53 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of neural networ…ks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several 'subnetworks' (modules), which may perform the same or re lated tasks, and then use an 'appropriate' method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of 'lumped' or 'monolithic' networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network.
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
Contatta il venditoreVenditore con 4 stelleCondizione: Usato - Come nuovo
EUR 171,68
EUR 29,34 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Like New. Like New. book.
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 86,24
EUR 6,80 spedizioneSpedito da Italia a U.S.A.Quantità: Più di 20 disponibili
Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer US Okt 2012, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields…of neural networks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several 'subnetworks' (modules), which may perform the same or re lated tasks, and then use an 'appropriate' method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of 'lumped' or 'monolithic' networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network. 332 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 155,49
EUR 7,63 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand pp. 332 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
Lingua: Inglese
Editore: Springer, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 155,36
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND pp. 332.
Lingua: Inglese
Editore: Springer, Springer Okt 2012, 2012
Serie: The Springer International Series in Engineering and Computer Science, Libro 95 di 260. Libro 95 di 260 - The Springer International Series in Engineering and Computer Science
- Brossura
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of n…eural networks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several 'subnetworks' (modules), which may perform the same or re lated tasks, and then use an 'appropriate' method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of 'lumped' or 'monolithic' networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 332 pp. Englisch.
