Search results: Found 9

Listing 1 - 9 of 9
Sort by
Neuromorphic Engineering Systems and Applications

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889194544 Year: Pages: 182 DOI: 10.3389/978-2-88919-454-4 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-02-05 17:24:33
License:

Loading...
Export citation

Choose an application

Abstract

Neuromorphic engineering has just reached its 25th year as a discipline. In the first two decades neuromorphic engineers focused on building models of sensors, such as silicon cochleas and retinas, and building blocks such as silicon neurons and synapses. These designs have honed our skills in implementing sensors and neural networks in VLSI using analog and mixed mode circuits. Over the last decade the address event representation has been used to interface devices and computers from different designers and even different groups. This facility has been essential for our ability to combine sensors, neural networks, and actuators into neuromorphic systems. More recently, several big projects have emerged to build very large scale neuromorphic systems. The Telluride Neuromorphic Engineering Workshop (since 1994) and the CapoCaccia Cognitive Neuromorphic Engineering Workshop (since 2009) have been instrumental not only in creating a strongly connected research community, but also in introducing different groups to each other’s hardware. Many neuromorphic systems are first created at one of these workshops. With this special research topic, we showcase the state-of-the-art in neuromorphic systems.

Hierarchical Object Representations in the Visual Cortex and Computer Vision

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197989 Year: Pages: 290 DOI: 10.3389/978-2-88919-798-9 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-02-03 17:04:57
License:

Loading...
Export citation

Choose an application

Abstract

Over the past 40 years, neurobiology and computational neuroscience has proved that deeper understanding of visual processes in humans and non-human primates can lead to important advancements in computational perception theories and systems. One of the main difficulties that arises when designing automatic vision systems is developing a mechanism that can recognize - or simply find - an object when faced with all the possible variations that may occur in a natural scene, with the ease of the primate visual system. The area of the brain in primates that is dedicated at analyzing visual information is the visual cortex. The visual cortex performs a wide variety of complex tasks by means of simple operations. These seemingly simple operations are applied to several layers of neurons organized into a hierarchy, the layers representing increasingly complex, abstract intermediate processing stages. In this Research Topic we propose to bring together current efforts in neurophysiology and computer vision in order 1) To understand how the visual cortex encodes an object from a starting point where neurons respond to lines, bars or edges to the representation of an object at the top of the hierarchy that is invariant to illumination, size, location, viewpoint, rotation and robust to occlusions and clutter; and 2) How the design of automatic vision systems benefit from that knowledge to get closer to human accuracy, efficiency and robustness to variations.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications

Author:
ISBN: 9783039285761 / 9783039285778 Year: Pages: 244 DOI: 10.3390/books978-3-03928-577-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:57
License:

Loading...
Export citation

Choose an application

Abstract

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.

Keywords

memristor --- artificial synapse --- neuromorphic computing --- memristor-CMOS hybrid circuit --- temporal pooling --- sensory and hippocampal responses --- cortical neurons --- hierarchical temporal memory --- neocortex --- memristor-CMOS hybrid circuit --- defect-tolerant spatial pooling --- boost-factor adjustment --- memristor crossbar --- neuromorphic hardware --- memristor --- compact model --- emulator --- neuromorphic --- synapse --- STDP --- pavlov --- neuromorphic systems --- spiking neural networks --- memristors --- spike-timing-dependent plasticity --- RRAM --- vertical RRAM --- neuromorphics --- neural network hardware --- reinforcement learning --- AI --- neuromorphic computing --- multiscale modeling --- memristor --- optimization --- RRAM --- simulation --- memristors --- neuromorphic engineering --- OxRAM --- self-organization maps --- synaptic device --- memristor --- neuromorphic computing --- artificial intelligence --- hardware-based deep learning ICs --- circuit design --- memristor --- RRAM --- variability --- time series modeling --- autocovariance --- graphene oxide --- laser --- memristor --- crossbar array --- neuromorphic computing --- wire resistance --- synaptic weight --- character recognition --- neuromorphic computing --- Flash memories --- memristive devices --- resistive switching --- synaptic plasticity --- artificial neural network --- spiking neural network --- pattern recognition --- strongly correlated oxides --- resistive switching --- neuromorphic computing --- transistor-like devices --- artificial intelligence --- neural networks --- resistive switching --- memristive devices --- deep learning networks --- spiking neural networks --- electronic synapses --- crossbar array --- pattern recognition

Synaptic Plasticity in Neuromorphic Systems

Authors: --- --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198771 Year: Pages: 176 DOI: 10.3389/978-2-88919-877-1 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
License:

Quantum Foundations. 90 Years of Uncertainty

Authors: --- --- ---
ISBN: 9783038977544 Year: Pages: 188 DOI: 10.3390/books978-3-03897-755-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Physics (General) --- Science (General)
Added to DOAB on : 2019-04-05 10:34:31
License:

Loading...
Export citation

Choose an application

Abstract

The name of Joseph Fourier is also inseparable from the study of the mathematics of heat. Modern research on heat equations explores the extension of the classical diffusion equation on Riemannian, sub-Riemannian manifolds, and Lie groups. In parallel, in geometric mechanics, Jean-Marie Souriau interpreted the temperature vector of Planck as a space-time vector, obtaining, in this way, a phenomenological model of continuous media, which presents some interesting properties.

Flexible Electronics: Fabrication and Ubiquitous Integration

Author:
ISBN: 9783038978282 9783038978299 Year: Pages: 160 DOI: 10.3390/books978-3-03897-829-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Electrical and Nuclear Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Flexible Electronics platforms are increasingly used in the fields of sensors, displays, and energy conversion with the ultimate goal of facilitating their ubiquitous integration in our daily lives. Some of the key advantages associated with flexible electronic platforms are: bendability, lightweight, elastic, conformally shaped, nonbreakable, roll-to-roll manufacturable, and large-area. To realize their full potential, however, it is necessary to develop new methods for the fabrication of multifunctional flexible electronics at a reduced cost and with an increased resistance to mechanical fatigue. Accordingly, this Special Issue seeks to showcase short communications, research papers, and review articles that focus on novel methodological development for the fabrication, and integration of flexible electronics in healthcare, environmental monitoring, displays and human-machine interactivity, robotics, communication and wireless networks, and energy conversion, management, and storage.

Emerging Memory and Computing Devices in the Era of Intelligent Machines

Author:
ISBN: 9783039285020 / 9783039285037 Year: Pages: 276 DOI: 10.3390/books978-3-03928-503-7 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-06-09 16:38:57
License:

Loading...
Export citation

Choose an application

Abstract

Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system.

Keywords

3D-stacked --- DRAM --- in-DRAM cache --- low-latency --- low-power --- resistive memory --- crossbar --- in-memory computing --- analogue computing --- matrix-vector multiplication --- ECG --- voltage-controlled magnetic anisotropy --- magnetoresistive random access memory --- magnetic tunnel junction --- bioelectronic devices --- bionanohybrid material --- biomemory --- biologic gate --- bioprocessor --- protein --- nucleic acid --- nanoparticles --- SONOS --- flash memory --- charge spreading --- plasma treatment --- Oxygen-related trap --- data retention --- BCH --- decoder --- iBM --- GPU --- hybrid --- flash memory --- Galois field --- CUDA --- in-memory computing --- logic-in-memory --- non-von Neumann architecture --- configurable logic-in-memory architecture --- memory wall --- convolutional neural networks --- emerging technologies --- perpendicular Nano Magnetic Logic (pNML) --- silicon oxide-based memristors --- resistance switching mechanism --- variability --- conductive filament --- Weibull distribution --- quantum point contact --- real-time system --- dynamic voltage scaling --- task placement --- low-power technique --- nonvolatile memory --- neuromorphic system --- Hebbian training --- guide training --- memristor --- image classification --- STT-MRAM --- flip-flop --- power gating --- low-power --- bipolar resistive switching characteristics --- annealing temperatures --- solution-based dielectric --- resistive random access memory (RRAM) --- multi-level cell --- phase change memory --- programmable ramp-down current pulses --- Fast Fourier Transform --- in-memory computing --- associative processor --- non-von neumann architecture --- in-memory computing --- memristor --- RISC-V --- Internet of things --- blockchain --- U-shape recessed channel --- floating gate --- neuromorphic computing --- MCU (microprogrammed control unit) --- chalcogenide --- electrochemical metallization cell --- electrochemical metallization (ECM) --- ion conduction --- memristor --- self-directed channel (SDC) --- memristor --- crossbar array --- wire resistance --- synaptic weight --- character recognition --- n/a

Miniaturized Transistors

Authors: ---
ISBN: 9783039210107 9783039210114 Year: Pages: 202 DOI: 10.3390/books978-3-03921-011-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

What is the future of CMOS? Sustaining increased transistor densities along the path of Moore's Law has become increasingly challenging with limited power budgets, interconnect bandwidths, and fabrication capabilities. In the last decade alone, transistors have undergone significant design makeovers; from planar transistors of ten years ago, technological advancements have accelerated to today's FinFETs, which hardly resemble their bulky ancestors. FinFETs could potentially take us to the 5-nm node, but what comes after it? From gate-all-around devices to single electron transistors and two-dimensional semiconductors, a torrent of research is being carried out in order to design the next transistor generation, engineer the optimal materials, improve the fabrication technology, and properly model future devices. We invite insight from investigators and scientists in the field to showcase their work in this Special Issue with research papers, short communications, and review articles that focus on trends in micro- and nanotechnology from fundamental research to applications.

Keywords

flux calculation --- etching simulation --- process simulation --- topography simulation --- CMOS --- field-effect transistor --- ferroelectrics --- MOS devices --- negative-capacitance --- piezoelectrics --- power consumption --- thin-film transistors (TFTs) --- compact model --- surface potential --- technology computer-aided design (TCAD) --- metal oxide semiconductor field effect transistor (MOSFET) --- topography simulation --- metal gate stack --- level set --- high-k --- fin field effect transistor (FinFET) --- line edge roughness --- metal gate granularity --- nanowire --- non-equilibrium Green’s function --- random discrete dopants --- SiGe --- variability --- band-to-band tunneling (BTBT) --- electrostatic discharge (ESD) --- tunnel field-effect transistor (TFET) --- Silicon-Germanium source/drain (SiGe S/D) --- technology computer aided design (TCAD) --- bulk NMOS devices --- radiation hardened by design (RHBD) --- total ionizing dose (TID) --- Sentaurus TCAD --- layout --- two-dimensional material --- field effect transistor --- indium selenide --- phonon scattering --- mobility --- high-? dielectric --- low-frequency noise --- silicon-on-insulator --- MOSFET --- inversion channel --- buried channel --- subthreshold bias range --- low voltage --- low energy --- theoretical model --- process simulation --- device simulation --- compact models --- process variations --- systematic variations --- statistical variations --- FinFETs --- nanowires --- nanosheets --- semi-floating gate --- synaptic transistor --- neuromorphic system --- spike-timing-dependent plasticity (STDP) --- highly miniaturized transistor structure --- low power consumption --- drain engineered --- tunnel field effect transistor (TFET) --- polarization --- ambipolar --- subthreshold --- ON-state --- doping incorporation --- plasma-aided molecular beam epitaxy (MBE) --- segregation --- silicon nanowire --- n/a

Nanoelectronic Materials, Devices and Modeling

Authors: ---
ISBN: 9783039212255 9783039212262 Year: Pages: 242 DOI: 10.3390/books978-3-03921-226-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-08-28 11:21:27
License:

Loading...
Export citation

Choose an application

Abstract

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.

Keywords

UAV --- vision localization --- hierarchical --- landing --- information integration --- memristor --- synaptic device --- spike-timing-dependent plasticity --- neuromorphic computation --- memristive device --- ZnO films --- conditioned reflex --- quantum dot --- sample grating --- cross-gain modulation --- bistability --- distributed Bragg --- semiconductor optical amplifier --- topological insulator --- field-effect transistor --- nanostructure synthesis --- optoelectronic devices --- topological magnetoelectric effect --- drain-induced barrier lowering (DIBL) --- gate-induced drain leakage (GIDL) --- silicon on insulator (SOI) --- graphene --- supercapacitor --- energy storage --- ionic liquid --- UV irradiation --- luminescent centres --- bismuth ions --- two-photon process --- oscillatory neural networks --- pattern recognition --- higher order synchronization --- thermal coupling --- vanadium dioxide --- band-to-band tunneling --- L-shaped tunnel field-effect-transistor --- double-gate tunnel field-effect-transistor --- corner-effect --- AlGaN/GaN --- high-electron mobility transistor (HEMTs) --- p-GaN --- enhancement-mode --- 2DEG density --- InAlN/GaN heterostructure --- polarization effect --- quantum mechanical --- gallium nitride --- MISHEMT --- dielectric layer --- interface traps --- current collapse --- PECVD --- gate-induced drain leakage (GIDL) --- drain-induced barrier lowering (DIBL) --- recessed channel array transistor (RCAT) --- on-current (Ion) --- off-current (Ioff) --- subthreshold slope (SS) --- threshold voltage (VTH) --- saddle FinFET (S-FinFET) --- potential drop width (PDW) --- shallow trench isolation (STI) --- source/drain (S/D) --- conductivity --- 2D material --- Green’s function --- reflection transmision method --- variational form --- dual-switching transistor --- third harmonic tuning --- low voltage --- high efficiency --- CMOS power amplifier IC --- insulator–metal transition (IMT) --- charge injection --- Mott transition --- conductive atomic force microscopy (cAFM) --- gate field effect --- atomic layer deposition (ALD) --- zinc oxide --- silicon --- ZnO/Si --- electron affinity --- bandgap tuning --- conduction band offset --- heterojunction --- solar cells --- PC1D --- vertical field-effect transistor (VFET) --- back current blocking layer (BCBL) --- gallium nitride (GaN) --- normally off power devices --- n/a

Listing 1 - 9 of 9
Sort by
Narrow your search