Skip to main content

Memristive Devices For Brain Inspired Computing

In Order to Read Online or Download Memristive Devices For Brain Inspired Computing Full eBooks in PDF, EPUB, Tuebl and Mobi you need to create a Free account. Get any books you like and read everywhere you want. Fast Download Speed ~ Commercial & Ad Free. We cannot guarantee that every book is in the library!

Memristive Devices for Brain Inspired Computing

Memristive Devices for Brain Inspired Computing Book
Author : Sabina Spiga,Abu Sebastian,Damien Querlioz,Bipin Rajendran
Publisher : Woodhead Publishing
Release : 2020-06-12
ISBN : 0081027877
Language : En, Es, Fr & De

GET BOOK

Book Description :

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

Neuromorphic Devices for Brain Inspired Computing Book
Author : Qing Wan,Yi Shi
Publisher : John Wiley & Sons
Release : 2022-01-12
ISBN : 3527349790
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book provides comprehensive and timely summary on the most recent achievements on neuromorphic devices based on five kinds of materials/configurations and two exciting and promising applications of this area.

Design of a Neuromemristive Echo State Network Architecture

Design of a Neuromemristive Echo State Network Architecture Book
Author : Qutaiba Mohammed Saleh
Publisher : Unknown
Release : 2015
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

"Echo state neural networks (ESNs) provide an efficient classification technique for spatiotemporal signals. The feedback connections in the ESN enable feature extraction in both spatial and temporal components in time series data. This property has been used in several application domains such as image and video analysis, anomaly detection, and speech recognition. The software implementations of the ESN demonstrated efficiency in processing such applications, and have low design cost and flexibility. However, hardware implementation is necessary for power constrained resources applications such as therapeutic and mobile devices. Moreover, software realization consumes an order or more power compared to the hardware realization. In this work, a hardware ESN architecture with neuromemristive system is proposed. A neuromemristive system is a brain inspired computing system that uses memristive devises for synaptic plasticity. The memristive devices in neuromemristive systems have several interesting properties such as small footprint, simple device structure, and most importantly zero static power dissipation. The proposed architecture is reconfigurable for different ESN topologies. 2-D mesh architecture and toroidal networks are exploited in the reservoir layer. The relation between performance of the proposed reservoir architecture and reservoir metrics are analyzed. The proposed architecture is tested on a suite of medical and human computer interaction applications. The benchmark suite includes epileptic seizure detection, speech emotion recognition, and electromyography (EMG) based finger motion recognition. The proposed ESN architecture demonstrated an accuracy of 90%, 96%, and 84% for epileptic seizure detection, speech emotion recognition and EMG prosthetic fingers control respectively."--Abstract.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications Book
Author : Jordi Suñé
Publisher : MDPI
Release : 2020-04-09
ISBN : 3039285769
Language : En, Es, Fr & De

GET BOOK

Book Description :

Artificial Intelligence (AI) has found many applications in the past decade due to the ever increasing computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses. Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information. The so-called Spiking Neural Networks behave similarly to how the brain functions and are very energy efficient. Up to this moment, both spiking and conventional neural networks have been implemented in software programs running on conventional computing units. However, this approach requires high computing power, a large physical space and is energy inefficient. Thus, there is an increasing interest in developing AI tools directly implemented in hardware. The first hardware demonstrations have been based on CMOS circuits for neurons and specific communication protocols for synapses. However, to further increase training speed and energy efficiency while decreasing system size, the combination of CMOS neurons with memristor synapses is being explored. The memristor is a resistor with memory which behaves similarly to biological synapses. This book explores the state-of-the-art of neuromorphic circuits implementing neural networks with memristors for AI applications.

Organic Flexible Electronics

Organic Flexible Electronics Book
Author : Piero Cosseddu,Mario Caironi
Publisher : Woodhead Publishing
Release : 2020-10-07
ISBN : 012818891X
Language : En, Es, Fr & De

GET BOOK

Book Description :

Organic Electronics is a novel field of electronics that has gained an incredible attention over the past few decades. New materials, device architectures and applications have been continuously introduced by the academic and also industrial communities, and novel topics have raised strong interest in such communities, as molecular doping, thermoelectrics, bioelectronics and many others. Organic Flexible Electronics is mainly divided into three sections. The first part is focused on the fundamentals of organic electronics, such as charge transport models in these systems and new approaches for the design and synthesis of novel molecules. The first section addresses the main challenges that are still open in this field, including the important role of interfaces for achieving high-performing devices or the novel approaches employed for improving reliability issues. The second part discusses the most innovative devices which have been developed in recent years, such as devices for energy harvesting, flexible batteries, high frequency circuits, and flexible devices for tattoo electronics and bioelectronics. Finally the book reviews the most important applications moving from more standard flexible back panels to wearable and textile electronics and more futuristic applications like ingestible systems. Reviews the fundamental properties and methods for optimizing organic electronic materials including chemical doping and techniques to address stability issues; Discusses the most promising organic electronic devices for energy, electronics, and biomedical applications; Addresses key applications of organic electronic devices in imagers, wearable electronics, bioelectronics.

Celebrating the International Year of the Periodic Table Beyond Mendeleev 150

Celebrating the International Year of the Periodic Table  Beyond Mendeleev 150 Book
Author : Mikhail V. Kurushkin,W. H. Eugen Schwarz,Eugene A. Goodilin
Publisher : Frontiers Media SA
Release : 2021-01-11
ISBN : 2889663191
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Celebrating the International Year of the Periodic Table Beyond Mendeleev 150 book written by Mikhail V. Kurushkin,W. H. Eugen Schwarz,Eugene A. Goodilin, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Architectures and Algorithms for Intrinsic Computation with Memristive Devices

Architectures and Algorithms for Intrinsic Computation with Memristive Devices Book
Author : Anonim
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Neuromorphic engineering is the research field dedicated to the study and design of brain-inspired hardware and software tools. Recent advances in emerging nanoelectronics promote the implementation of synaptic connections based on memristive devices. Their non-volatile modifiable conductance was shown to exhibit the synaptic properties often used in connecting and training neural layers. With their nanoscale size and non-volatile memory property, they promise a next step in designing more area and energy efficient neuromorphic hardware. My research deals with the challenges of harnessing memristive device properties that go beyond the behaviors utilized for synaptic weight storage. Based on devices that exhibit non-linear state changes and volatility, I present novel architectures and algorithms that can harness such features for computation. The crossbar architecture is a dense array of memristive devices placed in-between horizontal and vertical nanowires. The regularity of this structure does not inherently provide the means for nonlinear computation of applied input signals. Introducing a modulation scheme that relies on nonlinear memristive device properties, heterogeneous state patterns of applied spatiotemporal input data can be created within the crossbar. In this setup, the untrained and dynamically changing states of the memristive devices offer a useful platform for information processing. Based on the MNIST data set I'll demonstrate how the temporal aspect of memristive state volatility can be utilized to reduce system size and training complexity for high dimensional input data. With 3 times less neurons and 15 times less synapses to train as compared to other memristor-based implementations, I achieve comparable classification rates of up to 93%. Exploiting dynamic state changes rather than precisely tuned stable states, this approach can tolerate device variation up to 6 times higher than reported levels. Random assemblies of memristive networks are analyzed as a substrate for intrinsic computation in connection with reservoir computing; a computational framework that harnesses observations of inherent dynamics within complex networks. Architectural and device level considerations lead to new levels of task complexity, which random memristive networks are now able to solve. A hierarchical design composed of independent random networks benefits from a diverse set of topologies and achieves prediction errors (NRMSE) on the time-series prediction task NARMA-10 as low as 0.15 as compared to 0.35 for an echo state network. Physically plausible network modeling is performed to investigate the relationship between network dynamics and energy consumption. Generally, increased network activity comes at the cost of exponentially increasing energy consumption due to nonlinear voltage-current characteristics of memristive devices. A trade-off, that allows linear scaling of energy consumption, is provided by the hierarchical approach. Rather than designing individual memristive networks with high switching activity, a collection of less dynamic, but independent networks can provide more diverse network activity per unit of energy. My research extends the possibilities of including emerging nanoelectronics into neuromorphic hardware. It establishes memristive devices beyond storage and motivates future research to further embrace memristive device properties that can be linked to different synaptic functions. Pursuing to exploit the functional diversity of memristive devices will lead to novel architectures and algorithms that study rather than dictate the behavior of such devices, with the benefit of creating robust and efficient neuromorphic hardware.

Mem elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mem elements for Neuromorphic Circuits with Artificial Intelligence Applications Book
Author : Christos Volos,Viet-Thanh Pham
Publisher : Academic Press
Release : 2021-07-01
ISBN : 0128232021
Language : En, Es, Fr & De

GET BOOK

Book Description :

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications illustrates recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) and their applications in nonlinear dynamical systems, computer science, analog and digital systems, and in neuromorphic circuits and artificial intelligence. The book is mainly devoted to recent results, critical aspects and perspectives of ongoing research on relevant topics, all involving networks of mem-elements devices in diverse applications. Sections contribute to the discussion of memristive materials and transport mechanisms, presenting various types of physical structures that can be fabricated to realize mem-elements in integrated circuits and device modeling. As the last decade has seen an increasing interest in recent advances in mem-elements and their applications in neuromorphic circuits and artificial intelligence, this book will attract researchers in various fields. Covers a broad range of interdisciplinary topics between mathematics, circuits, realizations, and practical applications related to nonlinear dynamical systems, nanotechnology, analog and digital systems, computer science and artificial intelligence Presents recent advances in the field of mem-elements (memristor, memcapacitor, meminductor) Includes interesting applications of mem-elements in nonlinear dynamical systems, analog and digital systems, neuromorphic circuits, computer science and artificial intelligence

Real Time Modelling and Processing for Communication Systems

Real Time Modelling and Processing for Communication Systems Book
Author : Muhammad Alam,Wael Dghais,Yuanfang Chen
Publisher : Springer
Release : 2017-12-27
ISBN : 3319722158
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book presents cutting-edge work on real-time modelling and processing, a highly active research field in both the research and industrial domains. Going beyond conventional real-time systems, major efforts are required to develop accurate and computational efficient real-time modelling algorithms and design automation tools that reflect the technological advances in high-speed and ultra-low-power transceiver communication architectures based on nanoscale devices. The book addresses basic and more advanced topics, such as I/O buffer circuits for ensuring reliable chip-to-chip communication, I/O buffer behavioural modelling, multiport empirical models for memory interfaces, compact behavioural modelling for memristive devices, and resource reservation modelling for distributed embedded systems. The respective chapters detail new research findings, new models, algorithms, implementations and simulations of the above-mentioned topics. As such, the book will help both graduate students and researchers understand the latest research into real-time modelling and processing.

Resistive Switching Oxide Materials Mechanisms Devices and Operations

Resistive Switching  Oxide Materials  Mechanisms  Devices and Operations Book
Author : Jennifer Rupp,Daniele Ielmini,Ilia Valov
Publisher : Springer Nature
Release : 2021-10-15
ISBN : 3030424243
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book provides a broad examination of redox-based resistive switching memories (ReRAM), a promising technology for novel types of nanoelectronic devices, according to the International Technology Roadmap for Semiconductors, and the materials and physical processes used in these ionic transport-based switching devices. It covers defect kinetic models for switching, ReRAM deposition/fabrication methods, tuning thin film microstructures, and material/device characterization and modeling. A slate of world-renowned authors address the influence of type of ionic carriers, their mobility, the role of the local and chemical composition and environment, and facilitate readers’ understanding of the effects of composition and structure at different length scales (e.g., crystalline vs amorphous phases, impact of extended defects such as dislocations and grain boundaries). ReRAMs show outstanding potential for scaling down to the atomic level, fast operation in the nanosecond range, low power consumption, and non-volatile storage. The book is ideal for materials scientists and engineers concerned with novel types of nanoelectronic devices such as memories, memristors, and switches for logic and neuromorphic computing circuits beyond the von Neumann concept.

Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices

Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices Book
Author : Manan Suri
Publisher : Springer
Release : 2017-01-21
ISBN : 813223703X
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book covers all major aspects of cutting-edge research in the field of neuromorphic hardware engineering involving emerging nanoscale devices. Special emphasis is given to leading works in hybrid low-power CMOS-Nanodevice design. The book offers readers a bidirectional (top-down and bottom-up) perspective on designing efficient bio-inspired hardware. At the nanodevice level, it focuses on various flavors of emerging resistive memory (RRAM) technology. At the algorithm level, it addresses optimized implementations of supervised and stochastic learning paradigms such as: spike-time-dependent plasticity (STDP), long-term potentiation (LTP), long-term depression (LTD), extreme learning machines (ELM) and early adoptions of restricted Boltzmann machines (RBM) to name a few. The contributions discuss system-level power/energy/parasitic trade-offs, and complex real-world applications. The book is suited for both advanced researchers and students interested in the field.

Nanoelectronic Materials Devices and Modeling

Nanoelectronic Materials  Devices and Modeling Book
Author : Qiliang Li,Hao Zhu
Publisher : MDPI
Release : 2019-07-15
ISBN : 3039212257
Language : En, Es, Fr & De

GET BOOK

Book Description :

As CMOS scaling is approaching the fundamental physical limits, a wide range of new nanoelectronic materials and devices have been proposed and explored to extend and/or replace the current electronic devices and circuits so as to maintain progress with respect to speed and integration density. The major limitations, including low carrier mobility, degraded subthreshold slope, and heat dissipation, have become more challenging to address as the size of silicon-based metal oxide semiconductor field effect transistors (MOSFETs) has decreased to nanometers, while device integration density has increased. This book aims to present technical approaches that address the need for new nanoelectronic materials and devices. The focus is on new concepts and knowledge in nanoscience and nanotechnology for applications in logic, memory, sensors, photonics, and renewable energy. This research on nanoelectronic materials and devices will be instructive in finding solutions to address the challenges of current electronics in switching speed, power consumption, and heat dissipation and will be of great interest to academic society and the industry.

Deep Learning Classifiers with Memristive Networks

Deep Learning Classifiers with Memristive Networks Book
Author : Alex Pappachen James
Publisher : Springer
Release : 2019-04-08
ISBN : 3030145247
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer networks, convolution neural networks, hierarchical temporal memory, and long short term memories, and deep neuro-fuzzy networks. It then focuses on the design of these neural networks using memristor crossbar architectures in detail. The book integrates the theory with various applications of neuro-memristive circuits and systems. It provides an introductory tutorial on a range of issues in the design, evaluation techniques, and implementations of different deep neural network architectures with memristors.

Nonlinear Circuits and Systems with Memristors

Nonlinear Circuits and Systems with Memristors Book
Author : Fernando Corinto,Mauro Forti,Leon O. Chua
Publisher : Springer Nature
Release : 2021
ISBN : 3030556514
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book presents a new approach to the study of physical nonlinear circuits and advanced computing architectures with memristor devices. Such a unified approach to memristor theory has never been systematically presented in book form. After giving an introduction on memristor-based nonlinear dynamical circuits (e.g., periodic/chaotic oscillators) and their use as basic computing analogue elements, the authors delve into the nonlinear dynamical properties of circuits and systems with memristors and present the flux-charge analysis, a novel method for analyzing the nonlinear dynamics starting from writing Kirchhoff laws and constitutive relations of memristor circuit elements in the flux-charge domain. This analysis method reveals new peculiar and intriguing nonlinear phenomena in memristor circuits, such as the coexistence of different nonlinear dynamical behaviors, extreme multistability and bifurcations without parameters. The book also describes how arrays of memristor-based nonlinear oscillators and locally-coupled neural networks can be applied in the field of analog computing architectures. The book will be of interest to scientists and engineers involved in the conceptual design of physical memristor devices and systems, mathematical and circuit models of physical processes, circuits and networks design, system engineering, or data processing and system analysis.

Handbook of Memristor Networks

Handbook of Memristor Networks Book
Author : Leon Chua,Georgios Ch. Sirakoulis,Andrew Adamatzky
Publisher : Springer Nature
Release : 2019-11-12
ISBN : 331976375X
Language : En, Es, Fr & De

GET BOOK

Book Description :

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.

Memristor Networks

Memristor Networks Book
Author : Andrew Adamatzky,Leon Chua
Publisher : Springer Science & Business Media
Release : 2013-12-18
ISBN : 3319026305
Language : En, Es, Fr & De

GET BOOK

Book Description :

Using memristors one can achieve circuit functionalities that are not possible to establish with resistors, capacitors and inductors, therefore the memristor is of great pragmatic usefulness. Potential unique applications of memristors are in spintronic devices, ultra-dense information storage, neuromorphic circuits and programmable electronics. Memristor Networks focuses on the design, fabrication, modelling of and implementation of computation in spatially extended discrete media with many memristors. Top experts in computer science, mathematics, electronics, physics and computer engineering present foundations of the memristor theory and applications, demonstrate how to design neuromorphic network architectures based on memristor assembles, analyse varieties of the dynamic behaviour of memristive networks and show how to realise computing devices from memristors. All aspects of memristor networks are presented in detail, in a fully accessible style. An indispensable source of information and an inspiring reference text, Memristor Networks is an invaluable resource for future generations of computer scientists, mathematicians, physicists and engineers.

Synaptic Plasticity for Neuromorphic Systems

Synaptic Plasticity for Neuromorphic Systems Book
Author : Christian Mayr,Sadique Sheik,Chiara Bartolozzi,Elisabetta Chicca
Publisher : Frontiers Media SA
Release : 2016-06-26
ISBN : 2889198774
Language : En, Es, Fr & De

GET BOOK

Book Description :

One of the most striking properties of biological systems is their ability to learn and adapt to ever changing environmental conditions, tasks and stimuli. It emerges from a number of different forms of plasticity, that change the properties of the computing substrate, mainly acting on the modification of the strength of synaptic connections that gate the flow of information across neurons. Plasticity is an essential ingredient for building artificial autonomous cognitive agents that can learn to reliably and meaningfully interact with the real world. For this reason, the neuromorphic community at large has put substantial effort in the design of different forms of plasticity and in putting them to practical use. These plasticity forms comprise, among others, Short Term Depression and Facilitation, Homeostasis, Spike Frequency Adaptation and diverse forms of Hebbian learning (e.g. Spike Timing Dependent Plasticity). This special research topic collects the most advanced developments in the design of the diverse forms of plasticity, from the single circuit to the system level, as well as their exploitation in the implementation of cognitive systems.

Photo Electroactive Non Volatile Memories for Data Storage and Neuromorphic Computing

Photo Electroactive Non Volatile Memories for Data Storage and Neuromorphic Computing Book
Author : Suting Han,Ye Zhou
Publisher : Woodhead Publishing
Release : 2020-05-26
ISBN : 0128226064
Language : En, Es, Fr & De

GET BOOK

Book Description :

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

Recent Development in Optoelectronic Devices

Recent Development in Optoelectronic Devices Book
Author : Ruby Srivastava
Publisher : BoD – Books on Demand
Release : 2018-08-29
ISBN : 1789236029
Language : En, Es, Fr & De

GET BOOK

Book Description :

The book "Recent Developments in Optoelectronic Devices" is about the latest developments in optoelectronics. This book is divided into three categories: light emitting devices, sensors, and light harvesters. This book also discusses the theoretical aspects of device design for iridium complexes as organic light emitting diodes (OLEDs), strategies for developing novel nanostructured materials, silicon-rich oxide (SRO) electroluminescent devices, and multifunctional optoelectronic devices developed on resistive switching effects. The worldwide participation of authors has contributed to the unifying effect of science. Furthermore, interested readers will also find information on the screen printed technology using semiconductor devices, nonlinear phenomena in quantum devices, experimental set up of optoelectronics flexible logic gate to realize logic operations, autonomous vehicles, and the latest developments in perovskites as solar cells.

Enabling Technologies for Very Large Scale Synaptic Electronics

Enabling Technologies for Very Large Scale Synaptic Electronics Book
Author : Themis Prodromakis,Alexantrou Serb
Publisher : Frontiers Media SA
Release : 2018-07-05
ISBN : 2889455084
Language : En, Es, Fr & De

GET BOOK

Book Description :

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