Memristive Devices for Brain Inspired Computing

Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications—Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage applications and toward brain-inspired computing. The book provides readers with an understanding of four key concepts, including materials and device aspects with a view of current materials systems and their remaining barriers, algorithmic aspects comprising basic concepts of neuroscience as well as various computing concepts, the circuits and architectures implementing those algorithms based on memristive technologies, and target applications, including brain-inspired computing, computational memory, and deep learning. This comprehensive book is suitable for an interdisciplinary audience, including materials scientists, physicists, electrical engineers, and computer scientists. Provides readers an overview of four key concepts in this emerging research topic including materials and device aspects, algorithmic aspects, circuits and architectures and target applications Covers a broad range of applications, including brain-inspired computing, computational memory, deep learning and spiking neural networks Includes perspectives from a wide range of disciplines, including materials science, electrical engineering and computing, providing a unique interdisciplinary look at the field

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  • Author : Sabina Spiga
  • Publisher : Woodhead Publishing
  • Pages : 564 pages
  • ISBN : 0081027877
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMemristive Devices for Brain Inspired Computing

Memristive Devices for Brain-Inspired Computing

Memristive Devices for Brain-Inspired Computing
  • Author : Sabina Spiga,Abu Sebastian,Damien Querlioz,Bipin Rajendran
  • Publisher : Woodhead Publishing
  • Release : 12 June 2020
GET THIS BOOKMemristive Devices for Brain-Inspired Computing

Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications—Computational Memory, Deep Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage applications and toward brain-inspired computing. The book provides readers with an understanding of four key concepts, including materials and device aspects with a view of current materials systems and their remaining barriers, algorithmic aspects comprising basic concepts of neuroscience as well as various computing concepts, the

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
  • Author : Jordi Suñé
  • Publisher : MDPI
  • Release : 09 April 2020
GET THIS BOOKMemristors for Neuromorphic Circuits and Artificial Intelligence Applications

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

Resistive Switching

Resistive Switching
  • Author : Daniele Ielmini,Rainer Waser
  • Publisher : John Wiley & Sons
  • Release : 28 December 2015
GET THIS BOOKResistive Switching

With its comprehensive coverage, this reference introduces readers to the wide topic of resistance switching, providing the knowledge, tools, and methods needed to understand, characterize and apply resistive switching memories. Starting with those materials that display resistive switching behavior, the book explains the basics of resistive switching as well as switching mechanisms and models. An in-depth discussion of memory reliability is followed by chapters on memory cell structures and architectures, while a section on logic gates rounds off the text.

Sub-Micron Semiconductor Devices

Sub-Micron Semiconductor Devices
  • Author : Ashish Raman,Deep Shekhar,Naveen Kumar
  • Publisher : CRC Press
  • Release : 11 May 2022
GET THIS BOOKSub-Micron Semiconductor Devices

This comprehensive reference text discusses novel semiconductor devices, including nanostructure field-effect transistors, photodiodes, high electron mobility transistors, and oxide-based devices. The text covers submicron semiconductor devices, device modeling, novel materials for devices, novel semiconductor devices, optimization techniques, and their application in detail. It covers such important topics as negative capacitance devices, surface-plasmon resonance devices, Fermi-level pinning, external stimuli-based optimization techniques, optoelectronic devices, and architecture-based optimization techniques. The book: Covers novel semiconductor devices with submicron dimensions Discusses comprehensive device optimization techniques

Handbook of Memristor Networks

Handbook of Memristor Networks
  • Author : Leon Chua,Georgios Ch. Sirakoulis,Andrew Adamatzky
  • Publisher : Springer Nature
  • Release : 12 November 2019
GET THIS BOOKHandbook of Memristor Networks

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware. With contributions from leaders in computer

Organic Flexible Electronics

Organic Flexible Electronics
  • Author : Piero Cosseddu,Mario Caironi
  • Publisher : Woodhead Publishing
  • Release : 07 October 2020
GET THIS BOOKOrganic Flexible Electronics

Organic Electronics is a novel field of electronics that has gained an incredible attention over the past few decades. New materials, device architectures and applications have been continuously introduced by the academic and also industrial communities, and novel topics have raised strong interest in such communities, as molecular doping, thermoelectrics, bioelectronics and many others. Organic Flexible Electronics is mainly divided into three sections. The first part is focused on the fundamentals of organic electronics, such as charge transport models in

Memristor Networks

Memristor Networks
  • Author : Andrew Adamatzky,Leon Chua
  • Publisher : Springer Science & Business Media
  • Release : 18 December 2013
GET THIS BOOKMemristor Networks

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

Handbook of Unconventional Computing

Handbook of Unconventional Computing
  • Author : Andrew Adamatzky
  • Publisher : Wspc Book Unconventional Compu
  • Release : 18 May 2022
GET THIS BOOKHandbook of Unconventional Computing

Did you know that computation can be implemented with cytoskeleton networks, chemical reactions, liquid marbles, plants, polymers and dozens of other living and inanimate substrates? Do you know what is reversible computing or a DNA microscopy? Are you aware that randomness aids computation? Would you like to make logical circuits from enzymatic reactions? Have you ever tried to implement digital logic with Minecraft? Do you know that eroding sandstones can compute too? This volume will review most of the key

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications
  • Author : Christos Volos,Viet-Thanh Pham
  • Publisher : Academic Press
  • Release : 01 July 2021
GET THIS BOOKMem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types

Memristor and Memristive Neural Networks

Memristor and Memristive Neural Networks
  • Author : Alex James
  • Publisher : BoD – Books on Demand
  • Release : 04 April 2018
GET THIS BOOKMemristor and Memristive Neural Networks

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