Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Kluwer Academic, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer Netherlands Okt 2012, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: 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 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.
Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
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Published by Springer Netherlands, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Gebunden. Condition: 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 for performing straightforward and rela.
Published by Springer Netherlands, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: moluna, Greven, Germany
Condition: 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 for performing straightforward and rela.
Published by Springer Netherlands, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: 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).
Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: NEW. Editor(s): Mastebroek, Henk A.K.; Vos, J.E. Series: Mathematical Modelling: Theory and Applications. Num Pages: 271 pages, biography. BIC Classification: GPFC; PHS; PSAJ; PSAN. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 15. Weight in Grams: 427. . 2012. Softcover reprint of the original 1st ed. 2001. Paperback. . . . .
Published by Springer Netherlands, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: 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).
Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
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Published by Kluwer Academic Publishers, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: 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. . . . .
Published by Springer, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: GreatBookPricesUK, Castle Donington, DERBY, United Kingdom
Condition: As New. Unread book in perfect condition.
Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: GreatBookPricesUK, Castle Donington, DERBY, United Kingdom
Condition: As New. Unread book in perfect condition.
Published by Springer Netherlands Sep 2001, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Buch. Condition: 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 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.
Published by Springer, 2012
ISBN 10: 9401038643 ISBN 13: 9789401038645
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Condition: NEW. Editor(s): Mastebroek, Henk A.K.; Vos, J.E. Series: Mathematical Modelling: Theory and Applications. Num Pages: 271 pages, biography. BIC Classification: GPFC; PHS; PSAJ; PSAN. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 15. Weight in Grams: 427. . 2012. Softcover reprint of the original 1st ed. 2001. Paperback. . . . . Books ship from the US and Ireland.
Published by Kluwer Academic Publishers, 2001
ISBN 10: 0792371925 ISBN 13: 9780792371922
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Condition: 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.