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Author: Valeri Mladenov
Publisher: MDPI
ISBN: 3038971049
Category : Technology & Engineering
Languages : en
Pages : 184
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Book Description
The investigation of new memory schemes, neural networks, computer systems and many other improved electronic devices is very important for future generation's electronic circuits and for their widespread application in all the areas of industry. In this aspect the analysis of new efficient and advanced electronic elements and circuits is an essential field of the highly developed electrical and electronic engineering. The resistance-switching phenomenon, observed in many amorphous oxides has been investigated since 1970 and it is a promising technology for constructing new electronic memories. It has been established that such oxide materials have the ability for changing their conductance in accordance to the applied voltage and memorizing their state for a long-time interval. Similar behaviour has been predicted for the memristor element by Leon Chua in 1971. The memristor is proposed in accordance to symmetry considerations and the relationships between the four basic electric quantities - electric current i, voltage v, charge q and magnetic flux Ψ. The memristor is an essential passive one-port element together with the resistor, inductor, and capacitor. The Williams HP research group has made a link between resistive switching devices, and the memristor proposed by Chua. A number of scientific papers related to memristors and memristor devices have been issued and several memristor models have been proposed. The memristor is a highly nonlinear component. It relates the electric charge q and the flux linkage, expressed as a time integral of the voltage. The memristor element has the important capability for remembering the electric charge passed through its cross-section and its respective resistance, when the electrical signals are switched off. Due to its nano-scale dimensions, non-volatility and memorizing properties, the memristor is a sound potential candidate for application in computer high-density memories, artificial neural networks and in many other electronic devices.
Author: Valeri Mladenov
Publisher: MDPI
ISBN: 3038971049
Category : Technology & Engineering
Languages : en
Pages : 184
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Book Description
The investigation of new memory schemes, neural networks, computer systems and many other improved electronic devices is very important for future generation's electronic circuits and for their widespread application in all the areas of industry. In this aspect the analysis of new efficient and advanced electronic elements and circuits is an essential field of the highly developed electrical and electronic engineering. The resistance-switching phenomenon, observed in many amorphous oxides has been investigated since 1970 and it is a promising technology for constructing new electronic memories. It has been established that such oxide materials have the ability for changing their conductance in accordance to the applied voltage and memorizing their state for a long-time interval. Similar behaviour has been predicted for the memristor element by Leon Chua in 1971. The memristor is proposed in accordance to symmetry considerations and the relationships between the four basic electric quantities - electric current i, voltage v, charge q and magnetic flux Ψ. The memristor is an essential passive one-port element together with the resistor, inductor, and capacitor. The Williams HP research group has made a link between resistive switching devices, and the memristor proposed by Chua. A number of scientific papers related to memristors and memristor devices have been issued and several memristor models have been proposed. The memristor is a highly nonlinear component. It relates the electric charge q and the flux linkage, expressed as a time integral of the voltage. The memristor element has the important capability for remembering the electric charge passed through its cross-section and its respective resistance, when the electrical signals are switched off. Due to its nano-scale dimensions, non-volatility and memorizing properties, the memristor is a sound potential candidate for application in computer high-density memories, artificial neural networks and in many other electronic devices.
Author:
Publisher:
ISBN: 9783038971030
Category :
Languages : en
Pages :
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Book Description
Author: Arun Kumar Singh
Publisher: CRC Press
ISBN: 1000464989
Category : Technology & Engineering
Languages : en
Pages : 353
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Book Description
Nanoelectronic Devices for Hardware and Software Security has comprehensive coverage of the principles, basic concepts, structure, modeling, practices, and circuit applications of nanoelectronics in hardware/software security. It also covers the future research directions in this domain. In this evolving era, nanotechnology is converting semiconductor devices dimensions from micron technology to nanotechnology. Nanoelectronics would be the key enabler for innovation in nanoscale devices, circuits, and systems. The motive for this research book is to provide relevant theoretical frameworks that include device physics, modeling, circuit design, and the latest developments in experimental fabrication in the field of nanotechnology for hardware/software security. There are numerous challenges in the development of models for nanoscale devices (e.g., FinFET, gate-all-around devices, TFET, etc.), short channel effects, fringing effects, high leakage current, and power dissipation, among others. This book will help to identify areas where there are challenges and apply nanodevice and circuit techniques to address hardware/software security issues.
Author: Savo G. Glisic
Publisher: John Wiley & Sons
ISBN: 1119790298
Category : Computers
Languages : en
Pages : 884
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Book Description
ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.
Author: Fernando Corinto
Publisher: Springer Nature
ISBN: 3030556514
Category : Technology & Engineering
Languages : en
Pages : 438
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Book Description
This book presents a new approach to the study of physical nonlinear circuits and advanced computing architectures with memristor devices. Such a unified approach to memristor theory has never been systematically presented in book form. After giving an introduction on memristor-based nonlinear dynamical circuits (e.g., periodic/chaotic oscillators) and their use as basic computing analogue elements, the authors delve into the nonlinear dynamical properties of circuits and systems with memristors and present the flux-charge analysis, a novel method for analyzing the nonlinear dynamics starting from writing Kirchhoff laws and constitutive relations of memristor circuit elements in the flux-charge domain. This analysis method reveals new peculiar and intriguing nonlinear phenomena in memristor circuits, such as the coexistence of different nonlinear dynamical behaviors, extreme multistability and bifurcations without parameters. The book also describes how arrays of memristor-based nonlinear oscillators and locally-coupled neural networks can be applied in the field of analog computing architectures, for example for pattern recognition. The book will be of interest to scientists and engineers involved in the conceptual design of physical memristor devices and systems, mathematical and circuit models of physical processes, circuits and networks design, system engineering, or data processing and system analysis.
Author: Jordi Suñé
Publisher: MDPI
ISBN: 3039285769
Category : Technology & Engineering
Languages : en
Pages : 244
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Book Description
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.
Author: Ioannis Vourkas
Publisher: Springer
ISBN: 3319226479
Category : Technology & Engineering
Languages : en
Pages : 263
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Book Description
This book considers the design and development of nanoelectronic computing circuits, systems and architectures focusing particularly on memristors, which represent one of today’s latest technology breakthroughs in nanoelectronics. The book studies, explores, and addresses the related challenges and proposes solutions for the smooth transition from conventional circuit technologies to emerging computing memristive nanotechnologies. Its content spans from fundamental device modeling to emerging storage system architectures and novel circuit design methodologies, targeting advanced non-conventional analog/digital massively parallel computational structures. Several new results on memristor modeling, memristive interconnections, logic circuit design, memory circuit architectures, computer arithmetic systems, simulation software tools, and applications of memristors in computing are presented. High-density memristive data storage combined with memristive circuit-design paradigms and computational tools applied to solve NP-hard artificial intelligence problems, as well as memristive arithmetic-logic units, certainly pave the way for a very promising memristive era in future electronic systems. Furthermore, these graph-based NP-hard problems are solved on memristive networks, and coupled with Cellular Automata (CA)-inspired computational schemes that enable computation within memory. All chapters are written in an accessible manner and are lavishly illustrated. The book constitutes an informative cornerstone for young scientists and a comprehensive reference to the experienced reader, hoping to stimulate further research on memristive devices, circuits, and systems.
Author: Christos Volos
Publisher: Academic Press
ISBN: 0128232021
Category : Technology & Engineering
Languages : en
Pages : 570
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Book Description
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 of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in 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
Author: Andrew Adamatzky
Publisher: Springer Science & Business Media
ISBN: 3319026305
Category : Computers
Languages : en
Pages : 716
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Book Description
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.
Author: Krassimir Georgiev
Publisher: Springer
ISBN: 3319972774
Category : Technology & Engineering
Languages : en
Pages : 440
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Book Description
This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM’17, held in Sofia, Bulgaria, in December 2017. The general theme of BGSIAM’17 was industrial and applied mathematics, with a particular focus on: high-performance computing, numerical methods and algorithms, analysis of partial differential equations and their applications, mathematical biology, control and uncertain systems, stochastic models, molecular dynamics, neural networks, genetic algorithms, metaheuristics for optimization problems, generalized nets, and Big Data.
