9780792371922 - plausible neural networks for biological modelling: 13 (mathematical modelling: theory and applications, 13) (15 resultados)
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Plausible Neural Networks for Biological Modelling (Mathematical Modelling: Theory and Applications)
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Condición: 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. . . . .
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Condición: 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.
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Buch. Condición: 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 re…latively 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).
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Plausible Neural Networks for Biological Modelling (Mathematical Modelling: Theory and Applications)
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 su…itable for performing straightforward and rela.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 straig…htforward 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). 276 pp. Englisch.
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Buch. Condición: Neu. Plausible Neural Networks for Biological Modelling | J. E. Vos (u. a.) | Buch | ix | Englisch | 2001 | Springer Netherland | EAN 9780792371922 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on…Demand.
Idioma: Inglés
Editorial: Springer Netherlands, Springer Netherlands Sep 2001, 2001
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 straightfo…rward 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).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.
