Memristive Devices for Brain Inspired Computing

Memristive Devices for Brain Inspired Computing
Author: Sabina Spiga,Abu Sebastian,Damien Querlioz,Bipin Rajendran
Publsiher: Woodhead Publishing
Total Pages: 564
Release: 2020-06-12
ISBN 10: 0081027877
ISBN 13: 9780081027875
Language: EN, FR, DE, ES & NL

Memristive Devices for Brain Inspired Computing Book Review:

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

Resistive Switching

Resistive Switching
Author: Daniele Ielmini,Rainer Waser
Publsiher: John Wiley & Sons
Total Pages: 784
Release: 2015-12-23
ISBN 10: 3527680934
ISBN 13: 9783527680931
Language: EN, FR, DE, ES & NL

Resistive Switching Book Review:

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.

Handbook of Memristor Networks

Handbook of Memristor Networks
Author: Leon Chua,Georgios Ch. Sirakoulis,Andrew Adamatzky
Publsiher: Springer Nature
Total Pages: 1368
Release: 2019-11-12
ISBN 10: 331976375X
ISBN 13: 9783319763750
Language: EN, FR, DE, ES & NL

Handbook of Memristor Networks Book Review:

This Handbook presents all aspects of memristor networks in an easy to read and tutorial style. Including many colour illustrations, it covers the foundations of memristor theory and applications, the technology of memristive devices, revised models of the Hodgkin-Huxley Equations and ion channels, neuromorphic architectures, and analyses of the dynamic behaviour of memristive networks. It also shows how to realise computing devices, non-von Neumann architectures and provides future building blocks for deep learning hardware. With contributions from leaders in computer science, mathematics, electronics, physics, material science and engineering, the book offers an indispensable source of information and an inspiring reference text for future generations of computer scientists, mathematicians, physicists, material scientists and engineers working in this dynamic field.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications
Author: Jordi Suñé
Publsiher: MDPI
Total Pages: 244
Release: 2020-04-09
ISBN 10: 3039285769
ISBN 13: 9783039285761
Language: EN, FR, DE, ES & NL

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications Book Review:

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.

Memristor and Memristive Neural Networks

Memristor and Memristive Neural Networks
Author: Alex James
Publsiher: BoD – Books on Demand
Total Pages: 324
Release: 2018-04-04
ISBN 10: 9535139479
ISBN 13: 9789535139478
Language: EN, FR, DE, ES & NL

Memristor and Memristive Neural Networks Book Review:

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 is required to ensure that the devices can be put to use and improve emerging application. In this book, various memristor models are discussed, from a mathematical framework to implementations in SPICE and verilog, that will be useful for the practitioners and researchers to get a grounding on the topic. The applications of the memristor models in various neuromorphic networks are discussed covering various neural network models, implementations in A/D converter and hierarchical temporal memories.

Advances in Memristor Neural Networks

Advances in Memristor Neural Networks
Author: Calin Ciufudean
Publsiher: BoD – Books on Demand
Total Pages: 124
Release: 2018-10-03
ISBN 10: 1789841151
ISBN 13: 9781789841152
Language: EN, FR, DE, ES & NL

Advances in Memristor Neural Networks Book Review:

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 the achievement of the next generation of intelligent hybrid biostructures. Different modeling and simulation tools can deliver an alternative to funding the theoretical approach as well as practical implementation of memristive systems.

Memristor Networks

Memristor Networks
Author: Andrew Adamatzky,Leon Chua
Publsiher: Springer Science & Business Media
Total Pages: 720
Release: 2013-12-18
ISBN 10: 3319026305
ISBN 13: 9783319026305
Language: EN, FR, DE, ES & NL

Memristor Networks Book Review:

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.

Neuromorphic Photonics

Neuromorphic Photonics
Author: Paul R. Prucnal,Bhavin J. Shastri
Publsiher: CRC Press
Total Pages: 412
Release: 2017-05-08
ISBN 10: 1315353490
ISBN 13: 9781315353494
Language: EN, FR, DE, ES & NL

Neuromorphic Photonics Book Review:

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 written at a level accessible to graduate students, while also intending to serve as a comprehensive reference for experts in the field.

Advances in Memristors Memristive Devices and Systems

Advances in Memristors  Memristive Devices and Systems
Author: Sundarapandian Vaidyanathan,Christos Volos
Publsiher: Springer
Total Pages: 511
Release: 2017-02-15
ISBN 10: 3319517244
ISBN 13: 9783319517247
Language: EN, FR, DE, ES & NL

Advances in Memristors Memristive Devices and Systems Book Review:

This book reports on the latest advances in and applications of memristors, memristive devices and systems. It gathers 20 contributed chapters by subject experts, including pioneers in the field such as Leon Chua (UC Berkeley, USA) and R.S. Williams (HP Labs, USA), who are specialized in the various topics addressed in this book, and covers broad areas of memristors and memristive devices such as: memristor emulators, oscillators, chaotic and hyperchaotic memristive systems, control of memristive systems, memristor-based min-max circuits, canonic memristors, memristive-based neuromorphic applications, implementation of memristor-based chaotic oscillators, inverse memristors, linear memristor devices, delayed memristive systems, flux-controlled memristive emulators, etc. Throughout the book, special emphasis is given to papers offering practical solutions and design, modeling, and implementation insights to address current research problems in memristors, memristive devices and systems. As such, it offers a valuable reference book on memristors and memristive devices for graduate students and researchers with a basic knowledge of electrical and control systems engineering.

Advances in Neuromorphic Memristor Science and Applications

Advances in Neuromorphic Memristor Science and Applications
Author: Robert Kozma,Robinson E. Pino,Giovanni E. Pazienza
Publsiher: Springer Science & Business Media
Total Pages: 320
Release: 2012-06-28
ISBN 10: 9400744919
ISBN 13: 9789400744912
Language: EN, FR, DE, ES & NL

Advances in Neuromorphic Memristor Science and Applications Book Review:

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.

Memristor Based Nanoelectronic Computing Circuits and Architectures

Memristor Based Nanoelectronic Computing Circuits and Architectures
Author: Ioannis Vourkas,Georgios Ch. Sirakoulis
Publsiher: Springer
Total Pages: 241
Release: 2015-08-26
ISBN 10: 3319226479
ISBN 13: 9783319226477
Language: EN, FR, DE, ES & NL

Memristor Based Nanoelectronic Computing Circuits and Architectures Book Review:

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.

Biophysics of Computation

Biophysics of Computation
Author: Christof Koch
Publsiher: Oxford University Press
Total Pages: 562
Release: 2004-10-28
ISBN 10: 0195181999
ISBN 13: 9780195181999
Language: EN, FR, DE, ES & NL

Biophysics of Computation Book Review:

Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

Neuronal Dynamics

Neuronal Dynamics
Author: Wulfram Gerstner,Werner M. Kistler,Richard Naud,Liam Paninski
Publsiher: Cambridge University Press
Total Pages: 590
Release: 2014-07-24
ISBN 10: 1107060834
ISBN 13: 9781107060838
Language: EN, FR, DE, ES & NL

Neuronal Dynamics Book Review:

This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Special Topics in Information Technology

Special Topics in Information Technology
Author: Barbara Pernici
Publsiher: Springer Nature
Total Pages: 131
Release: 2020-01-01
ISBN 10: 3030320944
ISBN 13: 9783030320942
Language: EN, FR, DE, ES & NL

Special Topics in Information Technology Book Review:

This open access book presents nine outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the nine best theses defended in 2018-19 and selected for the IT PhD Award. Each of the nine authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.

Atomic Switch

Atomic Switch
Author: Masakazu Aono
Publsiher: Springer Nature
Total Pages: 266
Release: 2020-03-02
ISBN 10: 303034875X
ISBN 13: 9783030348755
Language: EN, FR, DE, ES & NL

Atomic Switch Book Review:

Written by the inventors and leading experts of this new field, the book results from the International Symposium on “Atomic Switch: Invention, Practical use and Future Prospects” which took place in Tsukuba, Japan on March 27th - 28th, 2017. The book chapters cover the different trends from the science and technology of atomic switches to their applications like brain-type information processing, artificial intelligence (AI) and completely novel functional electronic nanodevices. The current practical uses of the atomic switch are also described. As compared with the conventional semiconductor transistor switch, the atomic switch is more compact (~1/10) with much lower power consumption (~1/10) and scarcely influenced by strong electromagnetic noise and radiation including cosmic rays in space (~1/100). As such, this book is of interest to researchers, scholars and students willing to explore new materials, to refine the nanofabrication methods and to explore new and efficient device architectures.

Phase Change Memory

Phase Change Memory
Author: Andrea Redaelli
Publsiher: Springer
Total Pages: 330
Release: 2017-11-18
ISBN 10: 3319690531
ISBN 13: 9783319690537
Language: EN, FR, DE, ES & NL

Phase Change Memory Book Review:

This book describes the physics of phase change memory devices, starting from basic operation to reliability issues. The book gives a comprehensive overlook of PCM with particular attention to the electrical transport and the phase transition physics between the two states. The book also contains design engineering details on PCM cell architecture, PCM cell arrays (including electrical circuit management), as well as the full spectrum of possible future applications.

Celebrating the International Year of the Periodic Table Beyond Mendeleev 150

Celebrating the International Year of the Periodic Table  Beyond Mendeleev 150
Author: Mikhail V. Kurushkin,W. H. Eugen Schwarz,Eugene A. Goodilin
Publsiher: Frontiers Media SA
Total Pages: 329
Release: 2021-01-11
ISBN 10: 2889663191
ISBN 13: 9782889663194
Language: EN, FR, DE, ES & NL

Celebrating the International Year of the Periodic Table Beyond Mendeleev 150 Book Review:

Spike timing dependent plasticity

Spike timing dependent plasticity
Author: Henry Markram,Wulfram Gerstner,Per Jesper Sjöström
Publsiher: Frontiers E-books
Total Pages: 329
Release: 2021
ISBN 10: 2889190439
ISBN 13: 9782889190430
Language: EN, FR, DE, ES & NL

Spike timing dependent plasticity Book Review:

Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.

Resistive Random Access Memory RRAM

Resistive Random Access Memory  RRAM
Author: Shimeng Yu
Publsiher: Morgan & Claypool Publishers
Total Pages: 79
Release: 2016-03-18
ISBN 10: 162705930X
ISBN 13: 9781627059305
Language: EN, FR, DE, ES & NL

Resistive Random Access Memory RRAM Book Review:

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.

Cognitive Modeling of Human Memory and Learning

Cognitive Modeling of Human Memory and Learning
Author: Lidia Ghosh,Amit Konar,Pratyusha Rakshit
Publsiher: John Wiley & Sons
Total Pages: 272
Release: 2020-08-21
ISBN 10: 1119705878
ISBN 13: 9781119705871
Language: EN, FR, DE, ES & NL

Cognitive Modeling of Human Memory and Learning Book Review:

Proposes computational models of human memory and learning using a brain-computer interfacing (BCI) approach Human memory modeling is important from two perspectives. First, the precise fitting of the model to an individual's short-term or working memory may help in predicting memory performance of the subject in future. Second, memory models provide a biological insight to the encoding and recall mechanisms undertaken by the neurons present in active brain lobes, participating in the memorization process. This book models human memory from a cognitive standpoint by utilizing brain activations acquired from the cortex by electroencephalographic (EEG) and functional near-infrared-spectroscopic (f-NIRs) means. Cognitive Modeling of Human Memory and Learning A Non-invasive Brain-Computer Interfacing Approach begins with an overview of the early models of memory. The authors then propose a simplistic model of Working Memory (WM) built with fuzzy Hebbian learning. A second perspective of memory models is concerned with Short-Term Memory (STM)-modeling in the context of 2-dimensional object-shape reconstruction from visually examined memorized instances. A third model assesses the subjective motor learning skill in driving from erroneous motor actions. Other models introduce a novel strategy of designing a two-layered deep Long Short-Term Memory (LSTM) classifier network and also deal with cognitive load assessment in motor learning tasks associated with driving. The book ends with concluding remarks based on principles and experimental results acquired in previous chapters. Examines the scope of computational models of memory and learning with special emphasis on classification of memory tasks by deep learning-based models Proposes two algorithms of type-2 fuzzy reasoning: Interval Type-2 fuzzy reasoning (IT2FR) and General Type-2 Fuzzy Sets (GT2FS) Considers three classes of cognitive loads in the motor learning tasks for driving learners Cognitive Modeling of Human Memory and Learning A Non-invasive Brain-Computer Interfacing Approach will appeal to researchers in cognitive neuro-science and human/brain-computer interfaces. It is also beneficial to graduate students of computer science/electrical/electronic engineering.