9789401038645 - plausible neural networks for biological modelling: 13 (10 risultati)
Plausible Neural Networks for Biological Modelling (Mathematical Modelling: Theory and Applications)
Lingua: Inglese
Editore: Springer, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Lingua: Inglese
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Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Condizione: New. pp. 276.
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Lingua: Inglese
Editore: Springer, Springer, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. 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 straightforwar…d 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, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: Basi6 International, Irving, TX, U.S.A.Basi6 International
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Lingua: Inglese
Editore: Springer Netherlands Okt 2012, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: 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 performin…g 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). 276 pp. Englisch.
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Lingua: Inglese
Editore: Springer Netherlands, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: moluna, Greven, Germaniamoluna
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Condizione: 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 suitable fo…r performing straightforward and rela.
Lingua: Inglese
Editore: Springer, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 276 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: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 276.
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Lingua: Inglese
Editore: Springer, Springer Okt 2012, 2012
Serie: Libro 4 di 12 - Mathematical Modelling: Theory and Applications
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: 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 st…raightforward 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 KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch.
