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Memristor and Memristive Neural Networks

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Release : 2018-04-04
Genre : Computers
Kind : eBook
Book Rating : 479/5 ( reviews)

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Book Synopsis Memristor and Memristive Neural Networks by : Alex James

Download or read book Memristor and Memristive Neural Networks written by Alex James. This book was released on 2018-04-04. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.

Memristor Networks

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Author :
Release : 2013-12-18
Genre : Computers
Kind : eBook
Book Rating : 305/5 ( reviews)

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Book Synopsis Memristor Networks by : Andrew Adamatzky

Download or read book Memristor Networks written by Andrew Adamatzky. This book was released on 2013-12-18. Available in PDF, EPUB and Kindle. Book excerpt: Using memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the memristor is of great pragmatic usefulness. Potential unique applications of memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits and programmable electronics. Memristor Networks focuses on the design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many memristors. Top experts in computer science, mathematics, electronics, physics and computer engineering present foundations of the memristor theory and applications, demonstrate how to design neuromorphic network architectures based on memristor assembles, analyse varieties of the dynamic behaviour of memristive networks and show how to realise computing devices from memristors. All aspects of memristor networks are presented in detail, in a fully accessible style. An indispensable source of information and an inspiring reference text, Memristor Networks is an invaluable resource for future generations of computer scientists, mathematicians, physicists and engineers.

Memristor and Memristive Neural Networks

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Author :
Release : 2018
Genre : Electronic computers. Computer science
Kind : eBook
Book Rating : 092/5 ( reviews)

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Book Synopsis Memristor and Memristive Neural Networks by : Alex Pappachen James

Download or read book Memristor and Memristive Neural Networks written by Alex Pappachen James. This book was released on 2018. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a range of models, circuits and systems built with memristor devices and networks in applications to neural networks. It is divided into three parts: (1) Devices, (2) Models and (3) Applications. The resistive switching property is an important aspect of the memristors, and there are several designs of this discussed in this book, such as in metal oxide/organic semiconductor nonvolatile memories, nanoscale switching and degradation of resistive random access memory and graphene oxide-based memristor. The modelling of the memristors is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.

Deep Learning Classifiers with Memristive Networks

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Author :
Release : 2019-04-08
Genre : Technology & Engineering
Kind : eBook
Book Rating : 247/5 ( reviews)

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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. This book was released on 2019-04-08. 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.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

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Release : 2020-04-09
Genre : Technology & Engineering
Kind : eBook
Book Rating : 769/5 ( reviews)

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Book Synopsis Memristors for Neuromorphic Circuits and Artificial Intelligence Applications by : Jordi Suñé

Download or read book Memristors for Neuromorphic Circuits and Artificial Intelligence Applications written by Jordi Suñé. This book was released on 2020-04-09. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.

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