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Hardcover. Condition: Clean & Unmarked. A very clean and straight copy. Clean text and an uncreased spine. Nearly new. Tight. Sharp. 213 pp.
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![Stock image for Deep Learning Classifiers with Memristive Networks: Theory and Applications (Modeling and Optimization in Science and Technologies, 14, Band 14) [Hardcover] James, Alex Pappachen for sale by SpringBooks](https://pictures.abebooks.com/isbn/9783030145224-us-300.jpg)
US$ 76.23
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Add to basketHardcover. Condition: Very Good. 1. Auflage. unread, with some shelfwear.
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Deep Learning Classifiers with Memristive Networks: Theory and Applications (Modeling and Optimization in Science and Technologies, 14)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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US$ 219.79
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Deep Learning Classifiers With Memristive Networks : Theory and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Deep Learning Classifiers with Memristive Networks (Hardcover)
Published by Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
Hardcover. Condition: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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US$ 237.59
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Add to basketCondition: As New. Unread book in perfect condition.
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Condition: New.
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Deep Learning Classifiers With Memristive Networks : Theory and Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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US$ 242.94
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Deep Learning Classifiers with Memristive Networks
Published by Springer International Publishing, Springer International Publishing Apr 2019, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
US$ 218.49
Convert currencyUS$ 69.97 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: 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.
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Deep Learning Classifiers with Memristive Networks : Theory and Applications
Published by Springer International Publishing, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
US$ 218.49
Convert currencyUS$ 72.96 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketBuch. Condition: 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.
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US$ 289.82
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Add to basketHardcover. Condition: New. New. book.
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US$ 315.50
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Add to basketHardcover. Condition: Brand New. 228 pages. 9.25x6.10x0.67 inches. In Stock.
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Deep Learning Classifiers with Memristive Networks (Hardcover)
Published by Springer Nature Switzerland AG, Cham, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
US$ 380.03
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Deep Learning Classifiers with Memristive Networks
Published by Springer International Publishing, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
US$ 184.66
Convert currencyUS$ 57.13 shipping from Germany to U.S.A.Quantity: Over 20 available
Add to basketCondition: 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&.
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Deep Learning Classifiers with Memristive Networks
Published by Springer International Publishing Apr 2019, 2019
ISBN 10: 3030145220 ISBN 13: 9783030145224
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
US$ 218.49
Convert currencyUS$ 26.82 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: 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.
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US$ 279.91
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Add to basketCondition: New. Print on Demand.
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US$ 300.79
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Add to basketCondition: New. PRINT ON DEMAND.
