Diamantaras (19 Ergebnisse)
Sprache: Englisch
Verlag: Wiley & Sons, Incorporated, John, 1996
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A TOOLBOX FOR ECONOMIC DESIGN
Diamantaras, Dimitrios [author]; Cardamone, Emina I. . et al. [contributors]
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Hardcover. Octavo, x, 292 pages. In Good plus condition. Spine is blue with black print. Boards in blue illustrated paper. Glue residue on rear from removed label. Illustrated: b&w tables. NOTE: Shelved in Netdesk Column G. 1378675. FP New Rockville Stock.
Sprache: Englisch
Verlag: Wiley, New York, 1996
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24 cm. original hardcover. xii,256 pp. diagrams. bibliography. index. "Adaptive and Learning Systems for Signal Processing, Communications, and Control". -(owner's name, otherwise (very) good). 555g.
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Paperback. Zustand: Brand New. 2010 edition. 596 pages. 9.50x6.00x1.25 inches. In Stock.
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Zustand: 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. Zustand: 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 Europe…an 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. Zustand: 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 coopera…tion 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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Zustand: 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.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 575 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
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Taschenbuch. Zustand: 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 Europe…an 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.
Sprache: Englisch
Verlag: Wiley, 1996
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Zustand: 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.
Sprache: Englisch
Verlag: Wiley-Interscience, 1996
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Zustand: New. In.
Sprache: Englisch
Verlag: John Wiley & Sons, 1996
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Zustand: New. pp. 272.
Sprache: Englisch
Verlag: John Wiley & Sons, 1996
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Gebunden. Zustand: New. K. I. Diamantaras is a research scientist at Aristotle University in Thessaloniki, Greece. He received his PhD from Princeton University and was formerly a research scientist for Siemans Corporate Research.S. Y. Kung is Professor of Electrical Engineering a.
Sprache: Englisch
Verlag: Wiley-Interscience, 1996
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Hardcover. Zustand: Brand New. 1st edition. 272 pages. 9.75x6.50x0.75 inches. In Stock.
Sprache: Englisch
Verlag: John Wiley and Sons Ltd, 1996
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Zustand: New. Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Series: Adaptive and Learning Systems for Signal Processing, Com…munications and Control Series. Num Pages: 272 pages, Illustrations. BIC Classification: UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 240 x 166 x 21. Weight in Grams: 536. . 1996. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
