Deep Learning Classifiers with Memristive Networks is popular PDF and ePub book, written by Alex Pappachen James in 2019-04-08, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Deep Learning Classifiers with Memristive Networks can be Read Online from any device for your convenience.
Deep Learning Classifiers with Memristive Networks Book PDF Summary
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.
Detail Book of Deep Learning Classifiers with Memristive Networks PDF
- Author : Alex Pappachen James
- Release : 08 April 2019
- Publisher : Springer
- ISBN : 9783030145248
- Genre : Technology & Engineering
- Total Page : 213 pages
- Language : English
- PDF File Size : 9,9 Mb
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