Download or read book Neuro inspired Computing Using Resistive Synaptic Devices written by Shimeng Yu and published by Springer. This book was released on 2018-07-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the recent breakthroughs in hardware implementation of neuro-inspired computing using resistive synaptic devices. The authors describe how two-terminal solid-state resistive memories can emulate synaptic weights in a neural network. Readers will benefit from state-of-the-art summaries of resistive synaptic devices, from the individual cell characteristics to the large-scale array integration. This book also discusses peripheral neuron circuits design challenges and design strategies. Finally, the authors describe the impact of device non-ideal properties (e.g. noise, variation, yield) and their impact on the learning performance at the system-level, using a device-algorithm co-design methodology.

Download or read book Neuro inspired Computing Using Emerging Non Volatile Memories written by Yuhan Shi and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data movement between separate processing and memory units in traditional von Neumann computing systems is costly in terms of time and energy. The problem is aggravated by the recent explosive growth in data intensive applications related to artificial intelligence. In-memory computing has been proposed as an alternative approach where computational tasks can be performed directly in memory without shuttling back and forth between the processing and memory units. Memory is at the heart of in-memory computing. Technology scaling of mainstream memory technologies, such as static random-access memory (SRAM) and Dynamic random-access memory (DRAM), is increasingly constrained by fundamental technology limits. The recent research progress of various emerging nonvolatile memory (eNVM) device technologies, such as resistive random-access memory (RRAM), phase-change memory (PCM), conductive bridging random-access memory (CBRAM), ferroelectric random-access memory (FeRAM) and spin-transfer torque magnetoresistive random-access memory (STT-MRAM), have drawn tremendous attentions owing to its high speed, low cost, excellent scalability, enhanced storage density. Moreover, an eNVM based crossbar array can perform in-memory matrix vector multiplications in analog manner with high energy efficiency and provide potential opportunities for accelerating computation in various fields such as deep learning, scientific computing and computer vision. This dissertation presents research work on demonstrating a wide range of emerging memory device technologies (CBRAM, RRAM and STT-MRAM) for implementing neuro-inspired in-memory computing in several real-world applications using software and hardware co-design approach. Chapter 1 presents low energy subquantum CBRAM devices and a network pruning technique to reduce network-level energy consumption by hundreds to thousands fold. We showed low energy (10×-100× less than conventional memory technologies) and gradual switching characteristics of CBRAM as synaptic devices. We developed a network pruning algorithm that can be employed during spiking neural network (SNN) training to further reduce the energy by 10×. Using a 512 Kbit subquantum CBRAM array, we experimentally demonstrated high recognition accuracy on the MNIST dataset for digital implementation of unsupervised learning. Chapter 2 presents the details of SNN pruning algorithm that used in Chapter1. The pruning algorithms exploits the features of network weights and prune weights during the training based on neurons' spiking characteristics, leading significant energy saving when implemented in eNVM based in-memory computing hardware. Chapter 3 presents a benchmarking analysis for the potential use of STT-MRAM in in-memory computing against SRAM at deeply scaled technology nodes (14nm and 7nm). A C++ based benchmarking platform is developed and uses LeNet-5, a popular convolutional neural network model (CNN). The platform maps STT-MRAM based in-memory computing architectures to LeNet-5 and can estimate inference accuracy, energy, latency, and area accurately for proposed architectures at different technology nodes compared against SRAM. Chapter 4 presents an adaptive quantization technique that compensates the accuracy loss due to limited conductance levels of PCM based synaptic devices and enables high-accuracy SNN unsupervised learning with low-precision PCM devices. The proposed adaptive quantization technique uses software and hardware co-design approach by designing software algorithms with consideration of real synaptic device characteristics and hardware limitations. Chapter 5 presents a real-world neural engineering application using in-memory computing. It presents an interface between eNVM based crossbar with neural electrodes to implement a real-time and high-energy efficient in-memory spike sorting system. A real-time hardware demonstration is performed using CuOx based eNVM crossbar to sort spike data in different brain regions recorded from multi-electrode arrays in animal experiments, which further extend the eNVM memory technologies for neural engineering applications. Chapter 6 presents a real-world deep learning application using in-memory computing. We demonstrated a direct integration of Ag-based conductive bridge random access memory (Ag-CBRAM) crossbar arrays with Mott-ReLU activation neurons for scalable, energy and area efficient hardware implementation of DNNs. Chapter 7 is the conclusion of this dissertation. The future directions of in-memory computing system based on eNVM technologies are discussed.

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.

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

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.

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.

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:

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.

Download or read book Selected Topics in Biomedical Circuits and Systems written by Minkyu Je and published by CRC Press. This book was released on 2022-09-01 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrated circuits and microsystems play a vital role in a variety of biomedical applications including life-saving/changing miniature medical devices, surgical procedures with less invasiveness and morbidity, low-cost preventive healthcare solutions for daily life, solutions for effective chronic disease management, point-of-care diagnosis for early disease detection, high-throughput bio sequencing and drug screening and groundbreaking brain-machine interfaces based on a deep understanding of human intelligence. In response to such strong demands for biomedical circuits and systems, a considerable amount of effort has been devoted to the research and development in this area, both by industry and academia, over recent years. This book, which belongs to the “Tutorials in Circuits and Systems” series, provides readers with an overview of new developments in the field of biomedical circuits and systems. It covers basic information about system-level and circuit-level requirements, operation principles, key factors of considerations, and design/implementation techniques, as well as recent advances in integrated circuits and microsystems for emerging biomedical applications. Technical topics covered in this book include: Biomedical Microsystem Integration; Biomedical Sensor Interface Circuits; Neural Stimulation Circuits; Wireless Power Transfer Circuits for Biomedical Microsystems; Artificial Intelligence Processors for Biomedical Circuits and Systems; Neuro-Inspired Computing and Neuromorphic Processors for Biomedical Circuits and Systems. This book is ideal for personnel in medical devices and biomedical engineering industries as well as academic staff and postgraduate/research students in biomedical circuits and systems.

Download or read book Memristors written by Alex James and published by BoD – Books on Demand. This book was released on 2020-05-27 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Edited Volume Memristors - Circuits and Applications of Memristor Devices is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Engineering. The book comprises single chapters authored by various researchers and edited by an expert active in the physical sciences, engineering, and technology research areas. All chapters are complete in itself but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on physical sciences, engineering, and technology,and open new possible research paths for further novel developments.

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:

Download or read book Spintronics Based Neuromorphic Computing written by Debanjan Bhowmik and published by Springer Nature. This book was released on with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download or read book Neuro inspired Information Processing written by Alain Cappy and published by John Wiley & Sons. This book was released on 2020-06-16 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The material path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.

Download or read book Mem elements for Neuromorphic Circuits with Artificial Intelligence Applications written by Christos Volos and published by Academic Press. This book was released on 2021-06-17 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Brain Inspired Computing From Neuroscience to Neuromorphic Electronics driving new forms of Artificial Intelligence written by Jonathan Mapelli and published by Frontiers Media SA. This book was released on 2022-03-08 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Enabling Technologies for Very Large Scale Synaptic Electronics written by Themis Prodromakis and published by Frontiers Media SA. This book was released on 2018-07-05 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important part of the colossal effort associated with the understanding of the brain involves using electronics hardware technology in order to reproduce biological behavior in ‘silico’. The idea revolves around leveraging decades of experience in the electronics industry as well as new biological findings that are employed towards reproducing key behaviors of fundamental elements of the brain (notably neurons and synapses) at far greater speed-scale products than any software-only implementation can achieve for the given level of modelling detail. So far, the field of neuromorphic engineering has proven itself as a major source of innovation towards the ‘silicon brain’ goal, with the methods employed by its community largely focused on circuit design (analogue, digital and mixed signal) and standard, commercial, Complementary Metal-Oxide Silicon (CMOS) technology as the preferred `tools of choice’ when trying to simulate or emulate biological behavior. However, alongside the circuit-oriented sector of the community there exists another community developing new electronic technologies with the express aim of creating advanced devices, beyond the capabilities of CMOS, that can intrinsically simulate neuron- or synapse-like behavior. A notable example concerns nanoelectronic devices responding to well-defined input signals by suitably changing their internal state (‘weight’), thereby exhibiting `synapse-like’ plasticity. This is in stark contrast to circuit-oriented approaches where the `synaptic weight’ variable has to be first stored, typically as charge on a capacitor or digitally, and then appropriately changed via complicated circuitry. The shift of very much complexity from circuitry to devices could potentially be a major enabling factor for very-large scale `synaptic electronics’, particularly if the new devices can be operated at much lower power budgets than their corresponding 'traditional' circuit replacements. To bring this promise to fruition, synergy between the well-established practices of the circuit-oriented approach and the vastness of possibilities opened by the advent of novel nanoelectronic devices with rich internal dynamics is absolutely essential and will create the opportunity for radical innovation in both fields. The result of such synergy can be of potentially staggering impact to the progress of our efforts to both simulate the brain and ultimately understand it. In this Research Topic, we wish to provide an overview of what constitutes state-of-the-art in terms of enabling technologies for very large scale synaptic electronics, with particular stress on innovative nanoelectronic devices and circuit/system design techniques that can facilitate the development of very large scale brain-inspired electronic systems