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EUR 60,01
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Da: Revaluation Books, Exeter, Regno Unito
EUR 61,77
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Aggiungi al carrelloPaperback. Condizione: Brand New. 410 pages. 8.98x5.98x1.02 inches. In Stock.
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EUR 61,23
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Da: Majestic Books, Hounslow, Regno Unito
EUR 54,62
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 320.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Print on Demand pp. 320.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 54,90
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 320.
Da: moluna, Greven, Germania
EUR 46,31
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorIgor Aleksander is Professor of Computer Science at Imperial College in London.KlappentextAn overview and synopsis of European connectionist research from both classical and.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 57,40
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - McClelland and Rumelhart's Parallel Distributed Processing was the first book to present a definitive account of the newly revived connectionist/neural net paradigm for artificial intelligence and cognitive science. While Neural Computing Architectures addresses the same issues, there is little overlap in the research it reports. These 18 contributions provide a timely and informative overview and synopsis of both pioneering and recent European connectionist research. Several chapters focus on cognitive modeling; however, most of the work covered revolves around abstract neural network theory or engineering applications, bringing important complementary perspectives to currently published work in PDP. In four parts, chapters take up neural computing from the classical perspective, including both foundational and current work; the mathematical perspective (of logic, automata theory, and probability theory), presenting less well-known work in which the neuron is modeled as a logic truth function that can be implemented in a direct way as a silicon read only memory. They present new material both in the form of analytical tools and models and as suggestions for implementation in optical form, and summarize the PDP perspective in a single extended chapter covering PDP theory, application, and speculation in US research. Each part is introduced by the editor.