Mem elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem-elements for Neuromorphic Circuits and Artificial Intelligence Applications illustrates recent advances and achievements in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and especially in neuromorphic circuits and artificial intelligence. This book has a particular focus on mem-elements (memristor, memcapacitor, and meminductor) and their applications. It is mainly devoted to present the most recent results as well as critical aspects and perspectives of on-going research on relevant topics, all of them involving networks of mem-elements devices used in diverse applications. This book contributes to the discussion of memristive materials and transport mechanisms, to present various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling as an essential aspect of mem-elements research. The last decade the increasing interest of the research community for the recent advances on mem-elements and their applications in neuromorphic circuits and artificial intelligence will attract researchers of various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence

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  • Author : Christos Volos
  • Publisher : Academic Press
  • Pages : 500 pages
  • ISBN : 9780128211847
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMem elements for Neuromorphic Circuits with Artificial Intelligence Applications

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 : 15 July 2021
GET THIS BOOKMem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem-elements for Neuromorphic Circuits and Artificial Intelligence Applications illustrates recent advances and achievements in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and especially in neuromorphic circuits and artificial intelligence. This book has a particular focus on mem-elements (memristor, memcapacitor, and meminductor) and their applications. It is mainly devoted to present the most recent results as well as critical aspects and perspectives of on-going research on relevant topics,

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

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

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

Advances in Neuromorphic Memristor Science and Applications

Advances in Neuromorphic Memristor Science and Applications
  • Author : Robert Kozma,Robinson E. Pino,Giovanni E. Pazienza
  • Publisher : Springer Science & Business Media
  • Release : 28 June 2012
GET THIS BOOKAdvances in Neuromorphic Memristor Science and Applications

Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural

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

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

Neuromorphic Photonics

Neuromorphic Photonics
  • Author : Paul R. Prucnal,Bhavin J. Shastri
  • Publisher : CRC Press
  • Release : 08 May 2017
GET THIS BOOKNeuromorphic Photonics

This book sets out to build bridges between the domains of photonic device physics and neural networks, providing a comprehensive overview of the emerging field of "neuromorphic photonics." It includes a thorough discussion of evolution of neuromorphic photonics from the advent of fiber-optic neurons to today’s state-of-the-art integrated laser neurons, which are a current focus of international research. Neuromorphic Photonics explores candidate interconnection architectures and devices for integrated neuromorphic networks, along with key functionality such as learning. It is

Backstepping Control of Nonlinear Dynamical Systems

Backstepping Control of Nonlinear Dynamical Systems
  • Author : Sundarapandian Vaidyanathan,Ahmad Taher Azar
  • Publisher : Academic Press
  • Release : 15 August 2020
GET THIS BOOKBackstepping Control of Nonlinear Dynamical Systems

Backstepping Control of Nonlinear Dynamical Systems addresses both the fundamentals of backstepping control and advances in the field. The latest techniques explored include ‘active backstepping control’, ‘adaptive backstepping control’, ‘fuzzy backstepping control’ and ‘adaptive fuzzy backstepping control’. The reference book provides numerous simulations using MATLAB and circuit design. These illustrate the main results of theory and applications of backstepping control of nonlinear control systems. Backstepping control encompasses varied aspects of mechanical engineering and has many different applications within the field.

Synaptic Plasticity for Neuromorphic Systems

Synaptic Plasticity for Neuromorphic Systems
  • Author : Christian Mayr,Sadique Sheik,Chiara Bartolozzi,Elisabetta Chicca
  • Publisher : Frontiers Media SA
  • Release : 26 June 2016
GET THIS BOOKSynaptic Plasticity for Neuromorphic Systems

One of the most striking properties of biological systems is their ability to learn and adapt to ever changing environmental conditions, tasks and stimuli. It emerges from a number of different forms of plasticity, that change the properties of the computing substrate, mainly acting on the modification of the strength of synaptic connections that gate the flow of information across neurons. Plasticity is an essential ingredient for building artificial autonomous cognitive agents that can learn to reliably and meaningfully interact

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.

Advances in Neuromorphic Memristor Science and Applications

Advances in Neuromorphic Memristor Science and Applications
  • Author : Robert Kozma,Robinson E. Pino,Giovanni E. Pazienza
  • Publisher : Springer Science & Business Media
  • Release : 28 June 2012
GET THIS BOOKAdvances in Neuromorphic Memristor Science and Applications

Physical implementation of the memristor at industrial scale sparked the interest from various disciplines, ranging from physics, nanotechnology, electrical engineering, neuroscience, to intelligent robotics. As any promising new technology, it has raised hopes and questions; it is an extremely challenging task to live up to the high expectations and to devise revolutionary and feasible future applications for memristive devices. The possibility of gathering prominent scientists in the heart of the Silicon Valley given by the 2011 International Joint Conference on Neural

Advances in Memristor Neural Networks

Advances in Memristor Neural Networks
  • Author : Calin Ciufudean
  • Publisher : BoD – Books on Demand
  • Release : 03 October 2018
GET THIS BOOKAdvances in Memristor Neural Networks

Nowadays, scientific research deals with alternative solutions for creating non-traditional computing systems, such as neural network architectures where the stochastic nature and live dynamics of memristive models play a key role. The features of memristors make it possible to direct processing and analysis of both biosystems and systems driven by artificial intelligence, as well as develop plausible physical models of spiking neural networks with self-organization. This book deals with advanced applications illustrating these concepts, and delivers an important contribution for

Analog VLSI

Analog VLSI
  • Author : Shih-Chii Liu,Jörg Kramer,Giacomo Indiveri,Tobias Delbra1/4ck,Rodney Douglas
  • Publisher : MIT Press
  • Release : 17 April 2021
GET THIS BOOKAnalog VLSI

An introduction to the design of analog VLSI circuits. Neuromorphic engineers work to improve the performance of artificial systems through the development of chips and systems that process information collectively using primarily analog circuits. This book presents the central concepts required for the creative and successful design of analog VLSI circuits. The discussion is weighted toward novel circuits that emulate natural signal processing. Unlike most circuits in commercial or industrial applications, these circuits operate mainly in the subthreshold or weak

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