Memristive Devices for Brain-Inspired Computing

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Publisher : Woodhead Publishing
ISBN 13 : 0081027877
Total Pages : 569 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Memristive Devices for Brain-Inspired Computing by : Sabina Spiga

Download or read book Memristive Devices for Brain-Inspired Computing written by Sabina Spiga and published by Woodhead Publishing. This book was released on 2020-06-12 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

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Author :
Publisher : MDPI
ISBN 13 : 3039285769
Total Pages : 244 pages
Book Rating : 4.0/5 (392 download)

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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 and published by MDPI. This book was released on 2020-04-09 with total page 244 pages. 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.

Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing

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Publisher : Woodhead Publishing
ISBN 13 : 0128226064
Total Pages : 356 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing by : Su-Ting Han

Download or read book Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing written by Su-Ting Han and published by Woodhead Publishing. This book was released on 2020-05-26 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing summarizes advances in the development of photo-electroactive memories and neuromorphic computing systems, suggests possible solutions to the challenges of device design, and evaluates the prospects for commercial applications. Sections covers developments in electro-photoactive memory, and photonic neuromorphic and in-memory computing, including discussions on design concepts, operation principles and basic storage mechanism of optoelectronic memory devices, potential materials from organic molecules, semiconductor quantum dots to two-dimensional materials with desirable electrical and optical properties, device challenges, and possible strategies. This comprehensive, accessible and up-to-date book will be of particular interest to graduate students and researchers in solid-state electronics. It is an invaluable systematic introduction to the memory characteristics, operation principles and storage mechanisms of the latest reported electro-photoactive memory devices. - Reviews the most promising materials to enable emerging computing memory and data storage devices, including one- and two-dimensional materials, metal oxides, semiconductors, organic materials, and more - Discusses fundamental mechanisms and design strategies for two- and three-terminal device structures - Addresses device challenges and strategies to enable translation of optical and optoelectronic technologies

Towards Neuroscience-Inspired Intelligent Computing: Theory, Methods, and Applications

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2832519172
Total Pages : 136 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Towards Neuroscience-Inspired Intelligent Computing: Theory, Methods, and Applications by : Di Wu

Download or read book Towards Neuroscience-Inspired Intelligent Computing: Theory, Methods, and Applications written by Di Wu and published by Frontiers Media SA. This book was released on 2023-04-03 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Neuromorphic Computing

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Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1803561432
Total Pages : 298 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis Neuromorphic Computing by :

Download or read book Neuromorphic Computing written by and published by BoD – Books on Demand. This book was released on 2023-11-15 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the cutting-edge world of Neuromorphic Computing, a groundbreaking volume that unravels the secrets of brain-inspired computational paradigms. Spanning neuroscience, artificial intelligence, and hardware design, this book presents a comprehensive exploration of neuromorphic systems, empowering both experts and newcomers to embrace the limitless potential of brain-inspired computing. Discover the fundamental principles that underpin neural computation as we journey through the origins of neuromorphic architectures, meticulously crafted to mimic the brain’s intricate neural networks. Unlock the true essence of learning mechanisms – unsupervised, supervised, and reinforcement learning – and witness how these innovations are shaping the future of artificial intelligence.

Emerging Technologies and Systems for Biologically Plausible Implementations of Neural Functions

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2889760006
Total Pages : 244 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Emerging Technologies and Systems for Biologically Plausible Implementations of Neural Functions by : Erika Covi

Download or read book Emerging Technologies and Systems for Biologically Plausible Implementations of Neural Functions written by Erika Covi and published by Frontiers Media SA. This book was released on 2022-04-26 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning and Non-volatile Memories

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Author :
Publisher : Springer Nature
ISBN 13 : 303103841X
Total Pages : 178 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Machine Learning and Non-volatile Memories by : Rino Micheloni

Download or read book Machine Learning and Non-volatile Memories written by Rino Micheloni and published by Springer Nature. This book was released on 2022-05-25 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basics of both NAND flash storage and machine learning, detailing the storage problems the latter can help to solve. At a first sight, machine learning and non-volatile memories seem very far away from each other. Machine learning implies mathematics, algorithms and a lot of computation; non-volatile memories are solid-state devices used to store information, having the amazing capability of retaining the information even without power supply. This book will help the reader understand how these two worlds can work together, bringing a lot of value to each other. In particular, the book covers two main fields of application: analog neural networks (NNs) and solid-state drives (SSDs). After reviewing the basics of machine learning in Chapter 1, Chapter 2 shows how neural networks can mimic the human brain; to accomplish this result, neural networks have to perform a specific computation called vector-by-matrix (VbM) multiplication, which is particularly power hungry. In the digital domain, VbM is implemented by means of logic gates which dictate both the area occupation and the power consumption; the combination of the two poses serious challenges to the hardware scalability, thus limiting the size of the neural network itself, especially in terms of the number of processable inputs and outputs. Non-volatile memories (phase change memories in Chapter 3, resistive memories in Chapter 4, and 3D flash memories in Chapter 5 and Chapter 6) enable the analog implementation of the VbM (also called “neuromorphic architecture”), which can easily beat the equivalent digital implementation in terms of both speed and energy consumption. SSDs and flash memories are strictly coupled together; as 3D flash scales, there is a significant amount of work that has to be done in order to optimize the overall performances of SSDs. Machine learning has emerged as a viable solution in many stages of this process. After introducing the main flash reliability issues, Chapter 7 shows both supervised and un-supervised machine learning techniques that can be applied to NAND. In addition, Chapter 7 deals with algorithms and techniques for a pro-active reliability management of SSDs. Last but not least, the last section of Chapter 7 discusses the next challenge for machine learning in the context of the so-called computational storage. No doubt that machine learning and non-volatile memories can help each other, but we are just at the beginning of the journey; this book helps researchers understand the basics of each field by providing real application examples, hopefully, providing a good starting point for the next level of development.

Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119507383
Total Pages : 296 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design by : Nan Zheng

Download or read book Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design written by Nan Zheng and published by John Wiley & Sons. This book was released on 2019-12-31 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities—and provides co-design and co-optimization methodologies for building hardware neural networks that can learn. Presenting a complete picture from high-level algorithm to low-level implementation details, Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design also covers many fundamentals and essentials in neural networks (e.g., deep learning), as well as hardware implementation of neural networks. The book begins with an overview of neural networks. It then discusses algorithms for utilizing and training rate-based artificial neural networks. Next comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from digital accelerator to analog accelerator. A design example on building energy-efficient accelerator for adaptive dynamic programming with neural networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along with a look at the hardware for spiking neural networks. Then comes a chapter offering readers three design examples (two of which are based on conventional CMOS, and one on emerging nanotechnology) to implement the learning algorithm found in the previous chapter. The book concludes with an outlook on the future of neural network hardware. Includes cross-layer survey of hardware accelerators for neuromorphic algorithms Covers the co-design of architecture and algorithms with emerging devices for much-improved computing efficiency Focuses on the co-design of algorithms and hardware, which is especially critical for using emerging devices, such as traditional memristors or diffusive memristors, for neuromorphic computing Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design is an ideal resource for researchers, scientists, software engineers, and hardware engineers dealing with the ever-increasing requirement on power consumption and response time. It is also excellent for teaching and training undergraduate and graduate students about the latest generation neural networks with powerful learning capabilities.

Neuromorphic Devices for Brain-inspired Computing

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 3527349790
Total Pages : 258 pages
Book Rating : 4.5/5 (273 download)

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Book Synopsis Neuromorphic Devices for Brain-inspired Computing by : Qing Wan

Download or read book Neuromorphic Devices for Brain-inspired Computing written by Qing Wan and published by John Wiley & Sons. This book was released on 2022-05-16 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the cutting-edge of neuromorphic technologies with applications in Artificial Intelligence In Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics, a team of expert engineers delivers a comprehensive discussion of all aspects of neuromorphic electronics designed to assist researchers and professionals to understand and apply all manner of brain-inspired computing and perception technologies. The book covers both memristic and neuromorphic devices, including spintronic, multi-terminal, and neuromorphic perceptual applications. Summarizing recent progress made in five distinct configurations of brain-inspired computing, the authors explore this promising technology’s potential applications in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. The book also includes: A thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms Comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviors Practical discussions of neuromorphic devices based on chalcogenide and organic materials In-depth examinations of neuromorphic computing and perceptual systems with emerging devices Perfect for materials scientists, biochemists, and electronics engineers, Neuromorphic Devices for Brain-Inspired Computing: Artificial Intelligence, Perception, and Robotics will also earn a place in the libraries of neurochemists, neurobiologists, and neurophysiologists.

Bio-Inspired Information Pathways

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Publisher : Springer Nature
ISBN 13 : 3031367057
Total Pages : 439 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Bio-Inspired Information Pathways by : Martin Ziegler

Download or read book Bio-Inspired Information Pathways written by Martin Ziegler and published by Springer Nature. This book was released on with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Emerging Memory and Computing Devices in the Era of Intelligent Machines

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Author :
Publisher : MDPI
ISBN 13 : 3039285025
Total Pages : 276 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Emerging Memory and Computing Devices in the Era of Intelligent Machines by : Pedram Khalili Amiri

Download or read book Emerging Memory and Computing Devices in the Era of Intelligent Machines written by Pedram Khalili Amiri and published by MDPI. This book was released on 2020-04-16 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system. This is driven by the requirements of data-intensive applications in artificial intelligence, autonomous systems, and edge computing. We are at an exciting time in the semiconductor industry where several innovative device and technology concepts are being developed to respond to these demands, and capture shares of the fast growing market for AI-related hardware. This special issue is devoted to highlighting, discussing and presenting the latest advancements in this area, drawing on the best work on emerging memory devices including magnetic, resistive, phase change, and other types of memory. The special issue is interested in work that presents concepts, ideas, and recent progress ranging from materials, to memory devices, physics of switching mechanisms, circuits, and system applications, as well as progress in modeling and design tools. Contributions that bridge across several of these layers are especially encouraged.

Machine Vision and Augmented Intelligence—Theory and Applications

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Publisher : Springer Nature
ISBN 13 : 9811650780
Total Pages : 681 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Vision and Augmented Intelligence—Theory and Applications by : Manish Kumar Bajpai

Download or read book Machine Vision and Augmented Intelligence—Theory and Applications written by Manish Kumar Bajpai and published by Springer Nature. This book was released on 2021-11-10 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2021) held at IIIT, Jabalpur, in February 2021. The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the volume. The book theme encompasses all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions based on the capture and processing of images. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, COVID-19, image processing and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in healthcare, brain-computer interface, cybersecurity, and social network analysis, natural language processing, etc.

Spiking Neural Network Learning, Benchmarking, Programming and Executing

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2889637670
Total Pages : 234 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Spiking Neural Network Learning, Benchmarking, Programming and Executing by : Guoqi Li

Download or read book Spiking Neural Network Learning, Benchmarking, Programming and Executing written by Guoqi Li and published by Frontiers Media SA. This book was released on 2020-06-05 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Emerging Non-Volatile Memories

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Author :
Publisher : Springer
ISBN 13 : 1489975373
Total Pages : 280 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Emerging Non-Volatile Memories by : Seungbum Hong

Download or read book Emerging Non-Volatile Memories written by Seungbum Hong and published by Springer. This book was released on 2014-11-18 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to the fundamentals of emerging non-volatile memories and provides an overview of future trends in the field. Readers will find coverage of seven important memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), Multiferroic RAM (MFRAM), Phase-Change Memories (PCM), Oxide-based Resistive RAM (RRAM), Probe Storage, and Polymer Memories. Chapters are structured to reflect diffusions and clashes between different topics. Emerging Non-Volatile Memories is an ideal book for graduate students, faculty, and professionals working in the area of non-volatile memory. This book also: Covers key memory technologies, including Ferroelectric Random Access Memory (FeRAM), Ferromagnetic RAM (FMRAM), and Multiferroic RAM (MFRAM), among others. Provides an overview of non-volatile memory fundamentals. Broadens readers’ understanding of future trends in non-volatile memories.

Resistive Random Access Memory (RRAM)

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Author :
Publisher : Springer Nature
ISBN 13 : 3031020308
Total Pages : 71 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Resistive Random Access Memory (RRAM) by : Shimeng Yu

Download or read book Resistive Random Access Memory (RRAM) written by Shimeng Yu and published by Springer Nature. This book was released on 2022-06-01 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: RRAM technology has made significant progress in the past decade as a competitive candidate for the next generation non-volatile memory (NVM). This lecture is a comprehensive tutorial of metal oxide-based RRAM technology from device fabrication to array architecture design. State-of-the-art RRAM device performances, characterization, and modeling techniques are summarized, and the design considerations of the RRAM integration to large-scale array with peripheral circuits are discussed. Chapter 2 introduces the RRAM device fabrication techniques and methods to eliminate the forming process, and will show its scalability down to sub-10 nm regime. Then the device performances such as programming speed, variability control, and multi-level operation are presented, and finally the reliability issues such as cycling endurance and data retention are discussed. Chapter 3 discusses the RRAM physical mechanism, and the materials characterization techniques to observe the conductive filaments and the electrical characterization techniques to study the electronic conduction processes. It also presents the numerical device modeling techniques for simulating the evolution of the conductive filaments as well as the compact device modeling techniques for circuit-level design. Chapter 4 discusses the two common RRAM array architectures for large-scale integration: one-transistor-one-resistor (1T1R) and cross-point architecture with selector. The write/read schemes are presented and the peripheral circuitry design considerations are discussed. Finally, a 3D integration approach is introduced for building ultra-high density RRAM array. Chapter 5 is a brief summary and will give an outlook for RRAM’s potential novel applications beyond the NVM applications.

Springer Handbook of Semiconductor Devices

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Publisher : Springer Nature
ISBN 13 : 3030798275
Total Pages : 1680 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Springer Handbook of Semiconductor Devices by : Massimo Rudan

Download or read book Springer Handbook of Semiconductor Devices written by Massimo Rudan and published by Springer Nature. This book was released on 2022-11-10 with total page 1680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Springer Handbook comprehensively covers the topic of semiconductor devices, embracing all aspects from theoretical background to fabrication, modeling, and applications. Nearly 100 leading scientists from industry and academia were selected to write the handbook's chapters, which were conceived for professionals and practitioners, material scientists, physicists and electrical engineers working at universities, industrial R&D, and manufacturers. Starting from the description of the relevant technological aspects and fabrication steps, the handbook proceeds with a section fully devoted to the main conventional semiconductor devices like, e.g., bipolar transistors and MOS capacitors and transistors, used in the production of the standard integrated circuits, and the corresponding physical models. In the subsequent chapters, the scaling issues of the semiconductor-device technology are addressed, followed by the description of novel concept-based semiconductor devices. The last section illustrates the numerical simulation methods ranging from the fabrication processes to the device performances. Each chapter is self-contained, and refers to related topics treated in other chapters when necessary, so that the reader interested in a specific subject can easily identify a personal reading path through the vast contents of the handbook.

Resistive Switching

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Publisher :
ISBN 13 : 9783527680870
Total Pages : 755 pages
Book Rating : 4.6/5 (88 download)

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Book Synopsis Resistive Switching by : Daniele Ielmini

Download or read book Resistive Switching written by Daniele Ielmini and published by . This book was released on 2016 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. An invaluable self-contained book for materials scientists, electrical engineers and physicists dealing with memory research and development.