Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies, 14) - Image 1

£100.01

Springer Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies, 14)

Name: Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies, 14)
Brand: Springer
Price: 100.01 GBP
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AI & Machine Learning

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Description

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. From the Back Cover 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. About the Author

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3030145220
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 17 April 2019
Listed Since: 30 January 2019

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Springer Deep Learning Classifiers with Memristive Networks: Theory and Applications: 14 (Modeling and Optimization in Science and Technologies, 14)

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