Deep Learning Classifiers with Memristive Networks

Deep Learning Classifiers with Memristive Networks
Author :
Publisher : Springer
Total Pages : 216
Release :
ISBN-10 : 9783030145248
ISBN-13 : 3030145247
Rating : 4/5 (247 Downloads)

Book Synopsis Deep Learning Classifiers with Memristive Networks by : Alex Pappachen James

Download or read book Deep Learning Classifiers with Memristive Networks written by Alex Pappachen James and published by Springer. This book was released on 2019-04-08 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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