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Paperback. Condizione: new. Paperback. th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 1518, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsth atexcite or inhibit the signal being communicated. ANNs have the ability to learn by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters. th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 1518, 2010. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback or Softback. Condizione: New. Artificial Neural Networks - ICANN 2010: 20th International Conference, Thessaloniki, Greece, Septmeber 15-18, 2010, Proceedings, Part II. Book.

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Paperback. Condizione: Brand New. 543 pages. 9.00x6.00x1.25 inches. In Stock.

Paperback. Condizione: Brand New. 2010 edition. 596 pages. 9.50x6.00x1.25 inches. In Stock.

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Condizione: New. Fast track conference proceedingUnique visibilityState-of-the-art researchth This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- salon.

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability 'to learn' by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters.

Taschenbuch. Condizione: Neu. Artificial Neural Networks - ICANN 2010 | 20th International Conference, Thessaloniki, Greece, Septmeber 15-18, 2020, Proceedings, Part II | Konstantinos Diamantaras (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2010 | Springer | EAN 9783642158216 | Verantwortliche Person für die EU: Lauinger, Sonia, Sonia Lauinger, Lauinger Verlag, Heinrich-Köhler-Platz 8, 76187 Karlsruhe, mail[at]lauinger-verlag[dot]de | Anbieter: preigu.

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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 575 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 620 | Sprache: Englisch | Produktart: Bücher | th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15¿18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability ¿to learn¿ by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 560 | Sprache: Englisch | Produktart: Bücher | th This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15¿18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the ?eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito?eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti?cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability ¿to learn¿ by example (a large volume of cases) through several iterations without requiring a priori ?xed knowledge of the relationships between process parameters.

Condizione: New.

Taschenbuch. Condizione: Neu. Neuware - th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightstha texcite or inhibit the signal being communicated. ANNs have the ability 'to learn' by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters.

Condizione: As New. Unread book in perfect condition.

Taschenbuch. Condizione: Neu. Artificial Neural Networks - ICANN 2010 | 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part I | Konstantinos Diamantaras (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2010 | Springer | EAN 9783642158186 | Verantwortliche Person für die EU: Lauinger, Sonia, Sonia Lauinger, Lauinger Verlag, Heinrich-Köhler-Platz 8, 76187 Karlsruhe, mail[at]lauinger-verlag[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexcite or inhibit the signal being communicated. ANNs have the ability 'to learn' by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters.

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthat excite or inhibit the signal being communicated. ANNs have the ability 'to learn' by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters. 560 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fast track conference proceedingUnique visibilityState of the art researchth This volume is part of the three-volume proceedings of the 20 International Conference on Arti?cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during Se.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15¿18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthatexci te or inhibit the signal being communicated. ANNs have the ability ¿to learn¿ by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 560 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -th This volume is part of the three-volume proceedings of the 20 International Conference on Arti cial Neural Networks (ICANN 2010) that was held in Th- saloniki, Greece during September 15-18, 2010. ICANN is an annual meeting sponsored by the European Neural Network Society (ENNS) in cooperation with the International Neural Network So- ety (INNS) and the Japanese Neural Network Society (JNNS). This series of conferences has been held annually since 1991 in Europe, covering the eld of neurocomputing, learning systems and other related areas. As in the past 19 events, ICANN 2010 provided a distinguished, lively and interdisciplinary discussion forum for researches and scientists from around the globe. Ito eredagoodchanceto discussthe latestadvancesofresearchandalso all the developments and applications in the area of Arti cial Neural Networks (ANNs). ANNs provide an information processing structure inspired by biolo- cal nervous systems and they consist of a large number of highly interconnected processing elements (neurons). Each neuron is a simple processor with a limited computing capacity typically restricted to a rule for combining input signals (utilizing an activation function) in order to calculate the output one. Output signalsmaybesenttootherunitsalongconnectionsknownasweightsthat excite or inhibit the signal being communicated. ANNs have the ability 'to learn' by example (a large volume of cases) through several iterations without requiring a priori xed knowledge of the relationships between process parameters. 620 pp. Englisch.