Search results for "Computer Science - Emerging Technologies"

showing 10 items of 10 documents

Resistive communications based on neuristors

2017

Memristors are passive elements that allow us to store information using a single element per bit. However, this is not the only utility of the memristor. Considering the physical chemical structure of the element used, the memristor can function at the same time as memory and as a communication unit. This paper presents a new approach to the use of the memristor and develops the concept of resistive communication.

010302 applied physicsFOS: Computer and information sciencesResistive touchscreenCommunication unitHardware_MEMORYSTRUCTURESComputer science020208 electrical & electronic engineeringComputer Science - Emerging TechnologiesSingle element02 engineering and technologyFunction (mathematics)Memristor01 natural scienceslaw.inventionEmerging Technologies (cs.ET)Unified Modeling LanguagelawPhysical chemical0103 physical sciences0202 electrical engineering electronic engineering information engineeringElectronic engineeringElement (category theory)computercomputer.programming_language
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Machine learning-based spin structure detection

2023

One of the most important magnetic spin structure is the topologically stabilised skyrmion quasi-particle. Its interesting physical properties make them candidates for memory and efficient neuromorphic computation schemes. For the device operation, detection of the position, shape, and size of skyrmions is required and magnetic imaging is typically employed. A frequently used technique is magneto-optical Kerr microscopy where depending on the samples material composition, temperature, material growing procedures, etc., the measurements suffer from noise, low-contrast, intensity gradients, or other optical artifacts. Conventional image analysis packages require manual treatment, and a more a…

FOS: Computer and information sciencesComputer Science - Machine LearningEmerging Technologies (cs.ET)Physics - Data Analysis Statistics and ProbabilityComputer Science - Emerging TechnologiesFOS: Physical sciencesData Analysis Statistics and Probability (physics.data-an)Machine Learning (cs.LG)
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Importance of the window function choice for the predictive modelling of memristors

2018

Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absence…

FOS: Computer and information sciencesComputer Science::Hardware ArchitectureEmerging Technologies (cs.ET)Computer Science::Emerging TechnologiesComputer Science - Emerging Technologies
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Transient dynamics of pulse-driven memristors in the presence of a stable fixed point

2019

Abstract Some memristors are quite interesting from the point of view of dynamical systems. When driven by narrow pulses of alternating polarities, their dynamics has a stable fixed point, which may be useful for future applications. We study the transient dynamics of two types of memristors characterized by a stable fixed point using a time-averaged evolution equation. Time-averaged trajectories of the Biolek window function memristor and resistor-threshold type memristor circuit (an effective memristor) are determined analytically, and the times of relaxation to the stable fixed point are found. Our analytical results are in perfect agreement with the results of numerical simulations.

FOS: Computer and information sciencesDynamical systems theoryFOS: Physical sciencesComputer Science - Emerging TechnologiesMemristorFixed point01 natural sciencesWindow function010305 fluids & plasmaslaw.inventionMemristive systemComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologieslawStablefixed pointMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesAttractorStatistical physics010306 general physicsPhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsAttractorMemristorResistance switching memoryCondensed Matter PhysicsAtomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsPulse (physics)Emerging Technologies (cs.ET)Relaxation (physics)Transient (oscillation)Physica E-Low-Dimensional Systems & Nanostructures
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Perspective on unconventional computing using magnetic skyrmions

2023

Learning and pattern recognition inevitably requires memory of previous events, a feature that conventional CMOS hardware needs to artificially simulate. Dynamical systems naturally provide the memory, complexity, and nonlinearity needed for a plethora of different unconventional computing approaches. In this perspective article, we focus on the unconventional computing concept of reservoir computing and provide an overview of key physical reservoir works reported. We focus on the promising platform of magnetic structures and, in particular, skyrmions, which potentially allow for low-power applications. Moreover, we discuss skyrmion-based implementations of Brownian computing, which has rec…

FOS: Computer and information sciencesEmerging Technologies (cs.ET)Condensed Matter - Mesoscale and Nanoscale PhysicsMesoscale and Nanoscale Physics (cond-mat.mes-hall)FOS: Physical sciencesComputer Science - Emerging Technologies
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Modeling Networks of Probabilistic Memristors in SPICE

2021

Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…

FOS: Computer and information sciencesHardware_MEMORYSTRUCTURESCondensed Matter - Mesoscale and Nanoscale PhysicsFOS: Physical sciencesComputer Science - Emerging TechnologiesComputer Science::Hardware ArchitectureEmerging Technologies (cs.ET)Computer Science::Emerging TechnologiesmemristorsspicenetworksMesoscale and Nanoscale Physics (cond-mat.mes-hall)lcsh:Electrical engineering. Electronics. Nuclear engineeringprobabilistic computinglcsh:TK1-9971Radioengineering
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Probabilistic Memristive Networks: Application of a Master Equation to Networks of Binary ReRAM cells

2020

Abstract The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the ca…

FOS: Computer and information sciencesProbabilistic computingComputer scienceGeneral MathematicsGeneral Physics and AstronomyBinary numberFOS: Physical sciencesComputer Science - Emerging TechnologiesMemristorTopologylaw.inventionModeling and simulationComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologieslawMaster equationMesoscale and Nanoscale Physics (cond-mat.mes-hall)Probabilistic logicElectronic circuitCondensed Matter - Materials ScienceCondensed Matter - Mesoscale and Nanoscale PhysicsApplied MathematicsProbabilistic logicMaterials Science (cond-mat.mtrl-sci)Statistical and Nonlinear PhysicsMoment (mathematics)Emerging Technologies (cs.ET)State (computer science)NetworksMemristors
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Metastable memristive lines for signal transmission and information processing applications

2016

Traditional studies of memristive devices have mainly focused on their applications in nonvolatile information storage and information processing. Here, we demonstrate that the third fundamental component of information technologies-the transfer of information-can also be employed with memristive devices. For this purpose, we introduce a metastable memristive circuit. Combining metastable memristive circuits into a line, one obtains an architecture capable of transferring a signal edge from one space location to another. We emphasize that the suggested metastable memristive lines employ only resistive circuit components. Moreover, their networks (for example, Y-connected lines) have an info…

FOS: Computer and information sciencesResistive touchscreenTheoretical computer scienceCondensed Matter - Mesoscale and Nanoscale PhysicsComputer scienceInformation storageInformation processingComputer Science - Emerging TechnologiesFOS: Physical sciencesHardware_PERFORMANCEANDRELIABILITY02 engineering and technologySignal edge021001 nanoscience & nanotechnology01 natural sciencesLine (electrical engineering)Emerging Technologies (cs.ET)MetastabilityComponent (UML)Mesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesHardware_INTEGRATEDCIRCUITSElectronic engineering010306 general physics0210 nano-technologyElectronic circuitPhysical Review E
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Bifurcation analysis of a TaO memristor model

2019

This paper presents a study of bifurcation in the time-averaged dynamics of TaO memristors driven by narrow pulses of alternating polarities. The analysis, based on a physics-inspired model, focuses on the stable fixed points and on how these are affected by the pulse parameters. Our main finding is the identification of a driving regime when two stable fixed points exist simultaneously. To the best of our knowledge, such bistability is identified in a single memristor for the first time. This result can be readily tested experimentally, and is expected to be useful in future memristor circuit designs.

FOS: Computer and information sciencesstable fixed pointAcoustics and UltrasonicsBistabilityFOS: Physical sciencesComputer Science - Emerging Technologies02 engineering and technologyMemristorFixed pointTopology01 natural scienceslaw.inventionComputer Science::Emerging TechnologieslawMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesresistance switching memoriesmemristorBifurcation010302 applied physicsPhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsNonlinear Sciences - Chaotic Dynamics021001 nanoscience & nanotechnologyCondensed Matter PhysicsNonlinear Sciences - Adaptation and Self-Organizing SystemsSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsPulse (physics)Emerging Technologies (cs.ET)Bifurcation analysisbifurcationChaotic Dynamics (nlin.CD)0210 nano-technologyAdaptation and Self-Organizing Systems (nlin.AO)Journal of Physics D: Applied Physics
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Polymer‐Based Composites for Engineering Organic Memristive Devices

2022

Memristive materials are related to neuromorphic applications as they can combine information processing with memory storage in a single computational element, just as biological neurons. Many of these bioinspired materials emulate the characteristics of memory and learning processes that happen in the brain. In this work, we report the memristive properties of a two-terminal (2-T) organic device based on ionic migration mediated by an ion-transport polymer. The material possesses unique memristive properties: it is reversibly switchable, shows tens of conductive states, presents Hebbian learning demonstrated by spiking time dependent plasticity (STDP), and behaves with both short- (STM) an…

Semiconductors orgànicsFOS: Computer and information sciencesCondensed Matter - Materials ScienceComputer Science - Emerging TechnologiesMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesPhysics - Applied PhysicsApplied Physics (physics.app-ph)Condensed Matter - Soft Condensed MatterElectronic Optical and Magnetic MaterialsElectroquímicaEmerging Technologies (cs.ET)Soft Condensed Matter (cond-mat.soft)MaterialsAdvanced Electronic Materials
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