Hardcover. Condizione: New. US SELLER SHIPS FAST FROM USA.
EUR 2,87
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Aggiungi al carrelloCondizione: very good. Bezemer, F.; Van Den Brink, H. (illustratore). Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
EUR 19,34
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Aggiungi al carrelloHardcover. Condizione: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 2001. Editeur différent. Tome 13. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Edition 2001. Different publisher. Volume 13. Ammareal gives back up to 15% of this item's net price to charity organizations.
EUR 14,07
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Aggiungi al carrelloCondizione: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
EUR 11,00
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Aggiungi al carrelloCondizione: Good. Oorspronkelijke omslag met 7 CD's, 8vo.
EUR 17,50
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Aggiungi al carrelloCondizione: New. Geysen, François (illustratore).
EUR 23,08
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Aggiungi al carrelloCondizione: Very good.
Editore: Canis, Warffum, 2015
Da: Bij tij en ontij ..., Kloosterburen, NL, Paesi Bassi
EUR 10,00
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Aggiungi al carrelloHardcover, 24 cm, 128 pp. Ills.: kleurenillustraties. Cond.: goed / good. ISBN: 9789058219992.
Hard Cover. Condizione: Good. No Jacket. Ex-library with the usual features. The interior is clean and tight. Binding is good. Cover shows light wear. 259 pages. Ex-Library.
EUR 30,60
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Very good. Geysen, François (illustratore).
EUR 38,17
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Aggiungi al carrelloCondizione: Very good.
EUR 38,17
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Aggiungi al carrelloCondizione: Very good.
Condizione: New.
Paperback. Condizione: new. Paperback. The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence, they are suitable for performing straightforward and relatively simple tasks like classification, pattern recognition and prediction, as well as more sophisticated tasks like the processing of temporal sequences and the context dependent processing of complex problems. Also, a wide variety of control tasks can be executed by them, and the suggestion is relatively obvious that neural networks perform adequately in such cases because they are thought to mimic the biological nervous system which is also devoted to such tasks. As we shall see, this suggestion is false but does not do any harm as long as it is only the final performance of the algorithm which counts. Neural networks are also used in the modelling of the functioning of (sub systems in) the biological nervous system. It will be clear that in such cases it is certainly not irrelevant how similar their algorithm is to what is precisely going on in the nervous system. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies). Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies). Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
EUR 100,93
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 99,78
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 99,78
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: Kluwer Academic Publishers, Dordrecht, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This title has the intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, where they originated. It aims to introduce, in a didactic manner, two developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. In addition, the neuro-anatomical processes of synapse modification during development, training, and memory formation are discussed as realistic bases for weight-adjustment in neural networks. While neural networks have many applications outside biology, where it is irrelevant precisely which architecture and which algorithms are used, it is essential that there is a close relationship between the network's properties and whatever is the case in a neuro-biological phenomenon that is being modelled or simulated in terms of a neural network. A recurrent architecture, the use of spiking neurons and appropriate weight update rules contribute to the plausibility of a neural network in such a case.Therefore, in the first half of this book the foundations are laid for the application of neural networks as models for the various biological phenomena that are treated in the second half of this book. These include various neural network models of sensory and motor control tasks that implement one or several of the requirements for biological plausibility. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies). Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Condizione: As New. Unread book in perfect condition.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 111,72
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 112,10
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Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 112,89
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Aggiungi al carrelloCondizione: New.
Condizione: New. pp. 276.
Lingua: Inglese
Editore: Kluwer Academic Publishers, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 135,60
Quantità: 15 disponibili
Aggiungi al carrelloCondizione: New. With an intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, this work introduces in a didactic manner, two developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. Editor(s): Mastebroek, Henk A.K.; Vos, Johan E. Series: Mathematical Modelling: Theory and Applications. Num Pages: 271 pages, biography. BIC Classification: PSAN; UGK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 17. Weight in Grams: 565. . 2001. Hardback. . . . .
Lingua: Inglese
Editore: Kluwer Academic Publishers, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Da: Kennys Bookstore, Olney, MD, U.S.A.
Condizione: New. With an intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, this work introduces in a didactic manner, two developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. Editor(s): Mastebroek, Henk A.K.; Vos, Johan E. Series: Mathematical Modelling: Theory and Applications. Num Pages: 271 pages, biography. BIC Classification: PSAN; UGK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 244 x 170 x 17. Weight in Grams: 565. . 2001. Hardback. . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: Springer Netherlands, Springer Netherlands, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 112,77
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence, they are suitable for performing straightforward and relatively simple tasks like classification, pattern recognition and prediction, as well as more sophisticated tasks like the processing of temporal sequences and the context dependent processing of complex problems. Also, a wide variety of control tasks can be executed by them, and the suggestion is relatively obvious that neural networks perform adequately in such cases because they are thought to mimic the biological nervous system which is also devoted to such tasks. As we shall see, this suggestion is false but does not do any harm as long as it is only the final performance of the algorithm which counts. Neural networks are also used in the modelling of the functioning of (sub systems in) the biological nervous system. It will be clear that in such cases it is certainly not irrelevant how similar their algorithm is to what is precisely going on in the nervous system. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies).
Lingua: Inglese
Editore: Springer Netherlands, Springer Netherlands, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 114,36
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence, they are suitable for performing straightforward and relatively simple tasks like classification, pattern recognition and prediction, as well as more sophisticated tasks like the processing of temporal sequences and the context dependent processing of complex problems. Also, a wide variety of control tasks can be executed by them, and the suggestion is relatively obvious that neural networks perform adequately in such cases because they are thought to mimic the biological nervous system which is also devoted to such tasks. As we shall see, this suggestion is false but does not do any harm as long as it is only the final performance of the algorithm which counts. Neural networks are also used in the modelling of the functioning of (sub systems in) the biological nervous system. It will be clear that in such cases it is certainly not irrelevant how similar their algorithm is to what is precisely going on in the nervous system. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies).
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 181,26
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 171,79
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: Like New. Like New. book.
EUR 202,05
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.