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Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192397 Year: Pages: 123 DOI: 10.3389/978-2-88919-239-7 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-11-16 15:44:59
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The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain's neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

Miniaturized Transistors

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

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

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