Memristive Devices For Brain Inspired Computing
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Memristive Devices For Brain Inspired Computing
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Author : Sabina Spiga
language : en
Publisher: Woodhead Publishing
Release Date : 2020-06-12
Memristive Devices For Brain Inspired Computing written by Sabina Spiga and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-12 with Technology & Engineering categories.
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
Neuromorphic Devices For Brain Inspired Computing
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Author : Qing Wan
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-10
Neuromorphic Devices For Brain Inspired Computing written by Qing Wan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-10 with Technology & Engineering categories.
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.
Intelligence In Chip Integrated Sensors And Memristive Computing
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Author : Alex James
language : en
Publisher: CRC Press
Release Date : 2024-12-20
Intelligence In Chip Integrated Sensors And Memristive Computing written by Alex James and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-20 with Technology & Engineering categories.
Intelligence in Chips: Integrated Sensors and Memristive Computing is an authoritative resource that navigates the exciting landscape of in-memory computing, neuromorphic circuits, and memristive technologies. This book curates expert insights from leading researchers like Abu Sebastian, Alex James, Alon Ascoli, Arindam Basu, Cory Merkel, Fernando Corinto, Jason Eshraghian, Rainer Waser, Spiros Nikolaidis, Stephan Menzel, and Vishal Saxena, highlighting some of the important contributions in the field. Through a comprehensive collection of talks, readers will gain deep insights into how memristive neural computing is revolutionizing artificial intelligence. The book covers the latest innovations in memristor array computing, brain-inspired circuits, neuromorphic event-driven vision, bio-inspired computing, and nonlinear phenomena in biological systems. Each chapter is authored by a distinguished expert, offering a multi-perspective analysis on how emerging technologies are pushing the boundaries of edge-AI and mixed-signal hardware. Whether you're a researcher, engineer, or student, this book is an essential guide that explores the confluence of circuit theory, artificial intelligence, and memristor technology, providing readers with practical methodologies and visionary outlooks for the future.
Brain Inspired Physical Reservoir Computing Architectures Using Biomolecular Memristors
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Author : Nicholas Armendarez
language : en
Publisher:
Release Date : 2025
Brain Inspired Physical Reservoir Computing Architectures Using Biomolecular Memristors written by Nicholas Armendarez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Brain-inspired computing has primarily driven advancements in machine learning algorithms and hardware. The low energy consumption and exceptional classification and prediction capabilities of the human brain make it an intriguing model for computation and information processing. However, most research has focused on software implementations of neural networks, which demand immense computational power for training and operation. At its core, neural network research hinges on connections between nonlinear nodes that map input data into a high-dimensional space for easier categorization. Traditional computing executes these nonlinear functions digitally, storing connections as weights in memory that the processor must retrieve to perform calculations. In contrast, biological brains integrate nonlinear activation, evident in the analog dynamics of neurons and synapses, along with massively parallel connections between these computational units where memory and processing are co-located. Thus, the materials and methods of contemporary computing are incompatible with achieving brain-like computing. To address this challenge, this dissertation explores biological materials and assemblies for computation and information processing, specifically ion channels embedded in phospholipid membranes, and their application in neural network architectures. The lipid bilayer and its voltage-gated ion channels form the fundamental substrate of biological computation, enabling efficient information processing. The work first focused on investigating the properties and nonlinear dynamics of two-terminal biomolecular memristors made from droplet interface bilayers doped with ion channels, modeling their behavior using both linear and nonlinear first-order models and identifying the conditions under which each model applies. Next, these biomolecular memristors' inherent nonlinearities and dynamic memory were leveraged for reservoir computing, a recurrent neural network paradigm. Reservoir computing relies on a sparsely connected, randomly generated reservoir layer with nonlinear nodes, and recent research has demonstrated that various physical systems can serve as such reservoirs in analog form. In this work, ion channel devices were demonstrated to function as parallel, low-dimensional reservoirs for diverse classification tasks. Additionally, by employing a nonlinear memristor model, physical reservoir layers were trained ex-situ and successfully performed in-situ inference without significant accuracy loss. State-of-the-art parallel memristor reservoir computing architectures lack recurrence among nodes--a crucial property for effective computation. To overcome this, the unique attributes of biomolecular memristor assemblies were leveraged to introduce recurrence for the first time. Networks of these ion channel devices were constructed to generate high-dimensional dynamics capable of solving complex problems requiring substantial memory and nonlinearity. Ultimately, nonlinear networks exhibiting fading memory dynamics were developed. Through accurate modeling and simulations, it is demonstrated that coupled networks of memristive devices can significantly outperform existing parallel implementations in the literature.
Frontiers In Memristive Materials For Neuromorphic Processing Applications
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Author : National Academies of Sciences Engineering and Medicine
language : en
Publisher:
Release Date : 2021-09-22
Frontiers In Memristive Materials For Neuromorphic Processing Applications written by National Academies of Sciences Engineering and Medicine and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-22 with categories.
Current von Neumann style computing is energy inefficient and bandwidth limited as information is physically shuttled via electrons between processor, short term non-volatile memory, and long-term storage. Biologically inspired neuromorphic computing, with its inherent autonomous learning capabilities and much lower power requirements based on analog processing, is seen as an avenue for overcoming these limitations. The development of nanoelectronic memory resistors, or memristors, is essential to neuromorphic architectures as they allow logic-based elements for information processing to be combined directly with nonvolatile memory for efficient emulation of neurons and synapses found in the brain. Memristors are typically composed of a switchable material with nonlinear hysteretic behavior sandwiched between two conducting encoding elements. The design, dynamic control, scaling and fundamental understanding of these materials is essential for establishing memristive devices. To explore the state-of-the-art in the materials fundamentally underlying memristor technologies: their science, their mechanisms and their functional imperatives to realize neuromorphic computing machines, the National Academies of Sciences, Engineering, and Medicine's Board on Physics and Astronomy convened a workshop on February 28, 2020. This publication summarizes the presentation and discussion of the workshop.
Advances In Neuromorphic Memristor Science And Applications
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Author : Robert Kozma
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-06-28
Advances In Neuromorphic Memristor Science And Applications written by Robert Kozma and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-28 with Medical categories.
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 Networks held in San Jose, CA, has offered us the unique opportunity of organizing a series of special events on the present status and future perspectives in neuromorphic memristor science. This book presents a selection of the remarkable contributions given by the leaders of the field and it may serve as inspiration and future reference to all researchers that want to explore the extraordinary possibilities given by this revolutionary concept.
Memristors For Neuromorphic Circuits And Artificial Intelligence Applications
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Author : Jordi Suñé
language : en
Publisher: MDPI
Release Date : 2020-04-09
Memristors For Neuromorphic Circuits And Artificial Intelligence Applications written by Jordi Suñé and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Technology & Engineering categories.
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.
Embrace Future Tech
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Author : Isaac Berners-Lee
language : en
Publisher: Publifye AS
Release Date : 2025-01-06
Embrace Future Tech written by Isaac Berners-Lee and has been published by Publifye AS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Computers categories.
""Embrace Future Tech"" delves into the revolutionary hardware innovations poised to transform personal computing in the next decade, focusing on three groundbreaking technologies: quantum processing units, neuromorphic processors, and molecular storage systems. The book expertly bridges the gap between traditional computing architecture and emerging paradigms, tracing the evolution from vacuum tubes to modern semiconductors while explaining why current limitations necessitate these innovative solutions. Through a carefully structured approach, the book explores how quantum computing's massive parallel processing capabilities can merge with brain-inspired architectures to create unprecedented computing efficiency. Readers gain deep insights into superconducting circuits, silicon neurons, and memristive devices, supported by research data from leading laboratories and exclusive interviews with industry experts. The technical content remains accessible while maintaining scientific accuracy, making complex concepts digestible for readers with basic technology knowledge. The book distinguishes itself by providing both theoretical foundations and practical applications, from enhanced cryptography to advanced medical imaging processing. It offers a balanced perspective on competing hardware architectures and development approaches, acknowledging challenges while highlighting viable solutions. This comprehensive exploration serves as an essential guide for technology professionals and enthusiasts seeking to understand how quantum computing and neuromorphic processing will reshape our technological landscape.
Nature Inspired Robotics
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Author : Jagjit Singh Dhatterwal
language : en
Publisher: CRC Press
Release Date : 2024-07-24
Nature Inspired Robotics written by Jagjit Singh Dhatterwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Technology & Engineering categories.
This book introduces the theories and methods of Nature-Inspired Robotics in artificial intelligence. Software and hardware technologies, alongside theories and methods, illustrate the application of bio-inspired artificial intelligence. It includes discussions on topics such as Robot Control Manipulators, Geometric Transformation, Robotic Drive Systems and Nature Inspired Robotic Neural System. Elaborating upon recent progress made in five distinct configurations of nature-inspired computing, it explores the potential applications of this technology in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. · Discusses advances in cutting-edge technology in brain-inspired computing, perception technologies and aspects of neuromorphic electronics · Offers a thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms · Provides comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviours · Includes cognitive behaviour of Inspired Robotics and cognitive technologies with applications in Artificial Intelligence · Contains practical discussions of neuromorphic devices based on chalcogenide and organic materials. This text acts as a reference book for students, scholars, and industry professionals.
Bio Inspired Information Pathways
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Author : Martin Ziegler
language : en
Publisher: Springer Nature
Release Date : 2023-09-19
Bio Inspired Information Pathways written by Martin Ziegler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-19 with Technology & Engineering categories.
This open access book offers a timely and comprehensive review of the field of neurotronics. Gathering cutting-edge contributions from neuroscientists, biologists, psychologists, as well as physicists, microelectronics engineers and information scientists, it gives extensive information on fundamental information pathways in selected nervous systems. It also highlights their relevance as building blocks for novel computing architectures, such as bio-inspired electronic devices, neuromorphic architectures, memristive devices, adaptive sensors and emergent, pulsed-coupled oscillatory networks. All in all, this book offers a unique bridge between fundamental research in neuroscience, neural information processing, nonlinear dynamics, and self-organization, and advanced practical applications concerning the fabrication of hardware-oriented computing.