Memristor and Memristive Neural Networks (Alex James)

 
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Memristor and Memristive Neural Networks (Alex James)

This book covers a variety of memristor-based models, circuits, and systems with applications to neural networks. There are three sections: devices, models, and applications, in that order.

The book discusses numerous designs of memristors with resistive switching capabilities, including those used in metal oxide/organic semiconductor nonvolatile memories, resistive random access memory deterioration, and memristors based on graphene oxide.

To ensure that the devices may be used and to enhance new applications, memristors must be modeled.

This book discusses various memristor models that will help scholars and practitioners get a foundation in the field, from a mathematical framework to implementations in SPICE and Verilog. The use of memristor models in various neuromorphic networks is described. This includes performances in A/D converters, neural network models, and hierarchical temporal memories.

Ebook Details

About the Authors
Pappachen, Alex James earned his Ph.D. from Griffith University's Queensland Micro- and Nanotechnology Centre in Brisbane, QLD, Australia. His contributions to memristive networks, neuromorphic computing, and image processing have earned him recognition on a global scale.
Publisher
Published
Published Date / Year
(April 4, 2018)
Hardcover
188 pages
Language
English
ISBN-13
978-953-51-3948-5 (eBook); 978-953-51-3947-8 (print)

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