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Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies) - Tapa dura
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This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.
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This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.
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Deep Learning Classifiers with Memristive Networks: Theory and Applications (Modeling and Optimization in Science and Technologies, 14, Band 14) [Hardcover] James, Alex Pappachen
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Springer, 2019
ISBN 10: 3030145220
ISBN 13: 9783030145224
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Librería: SpringBooks, Berlin, Alemania
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Hardcover. Condición: Very Good. 1. Auflage. unread, with some shelfwear. Nº de ref. del artículo: CEA-2306C-UHU-08-1000XS
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Deep Learning Classifiers with Memristive Networks: Theory and Applications (Modeling and Optimization in Science and Technologies, 14)
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Hardcover. Condición: Clean & Unmarked. A very clean and straight copy. Clean text and an uncreased spine. Nearly new. Tight. Sharp. 213 pp. Nº de ref. del artículo: 250603007
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Deep Learning Classifiers with Memristive Networks
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Springer International Publishing, 2019
ISBN 10: 3030145220
ISBN 13: 9783030145224
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Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers an introduction to deep neural network architecturesDescribes in detail different kind of neuro-memristive systems, circuits and modelsShows how to implement different kind of neural networks in analog memristive&. Nº de ref. del artículo: 268493096
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Deep Learning Classifiers with Memristive Networks
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Springer International Publishing Apr 2019, 2019
ISBN 10: 3030145220
ISBN 13: 9783030145224
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors. 228 pp. Englisch. Nº de ref. del artículo: 9783030145224
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Deep Learning Classifiers with Memristive Networks : Theory and Applications
Publicado por
Springer International Publishing, 2019
ISBN 10: 3030145220
ISBN 13: 9783030145224
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors. Nº de ref. del artículo: 9783030145224
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Deep Learning Classifiers with Memristive Networks: Theory and Applications (Modeling and Optimization in Science and Technologies, 14)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Deep Learning Classifiers With Memristive Networks : Theory and Applications
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Condición: New. Nº de ref. del artículo: 35162156-n
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Deep Learning Classifiers With Memristive Networks : Theory and Applications
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Deep Learning Classifiers with Memristive Networks
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Springer International Publishing, Springer International Publishing Apr 2019, 2019
ISBN 10: 3030145220
ISBN 13: 9783030145224
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. Nº de ref. del artículo: 9783030145224
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Deep Learning Classifiers With Memristive Networks : Theory and Applications
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 35162156
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