Search results for "Computer simulation"

showing 10 items of 1054 documents

A model for long-term potentiation and depression

1995

A computational model of long-term potentiation (LTP) and long-term depression (LTD) in the hippocampus is presented. The model assumes the existence of retrograde signals, is in good agreement with several experimental data on LTP, LTD, and their pharmacological manipulations, and shows how a simple kinetic scheme can capture the essential characteristics of the processes involved in LTP and LTD. We propose that LTP and LTD could be two different but conceptually similar processes, induced by the same class of retrograde signals, and maintained by two distinct mechanisms. An interpretation of a number of experiments in terms of the molecular processes involved in LTP and LTD induction and …

Neuronal PlasticityTime FactorsKinetic modelmusculoskeletal neural and ocular physiologyCognitive NeuroscienceLong-Term PotentiationModels NeurologicalHippocampusLong-term potentiationHippocampusSensory SystemsKineticsCellular and Molecular Neurosciencenervous systemSynapsesRetrograde signalingAnimalsHumansComputer SimulationPsychologyNeuroscienceMathematicsSignal TransductionJournal of Computational Neuroscience
researchProduct

Sensorless induction machine drive for fly-wheel generation unit based on a TLS-based non-linear observer

2016

This paper proposes a sensorless technique for an induction machine Flywheel Energy Storage System (FESS) based on a non-linear observer integrated with a total least-squares speed estimator taking into consideration the IM (Induction Machine) saturation effects. The nonlinear observer is based on an original formulation of the dynamic model of the IM including the magnetic saturation, rearranged in a space-state form, after assuming as state variables the stator current and the rotor magnetizing current space-vectors in the stator reference frame. The choice of the observer gain has been made by the use of Lyapunov's method. The speed signal needed by the non-linear observer for the flux e…

Non-linear observerLyapunov functionState variableEngineeringTotal least squaresComputer simulationSensor-less techniquebusiness.industryStatorMagnetic separationEstimatorControl engineeringFlywheellaw.inventionsymbols.namesakeInduction machine driveSettore ING-INF/04 - AutomaticaControl theorylawsymbolsbusinessFlywheel energy storage systemReference frame2016 IEEE Symposium on Sensorless Control for Electrical Drives (SLED)
researchProduct

Supercontinuum optimization for dual-soliton based light sources using genetic algorithms in a grid platform

2014

We present a numerical strategy to design fiber based dual pulse light sources exhibiting two predefined spectral peaks in the anomalous group velocity dispersion regime. The frequency conversion is based on the soliton fission and soliton self-frequency shift occurring during super- continuum generation. The optimization process is carried out by a genetic algorithm that provides the optimum input pulse parameters: wavelength, temporal width and peak power. This algorithm is implemented in a Grid platform in order to take advantage of distributed computing. These results are useful for optical coherence tomography applications where bell-shaped pulses located in the second near-infrared wi…

Nonlinear opticsLightFOS: Physical sciencesSoliton (optics)Pulse propagation and temporal solitonsOpticsIllumination designOptical coherence tomographyGenetic algorithmmedicineCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALFiber Optic TechnologyScattering RadiationComputer SimulationElectrodesPhysicsPhotonsmedicine.diagnostic_testOptical coherence tomographybusiness.industryNonlinear opticsEquipment DesignAtomic and Molecular Physics and OpticsSupercontinuumPulse (physics)Power (physics)WavelengthComputer-Aided DesignbusinessAlgorithmsOptics (physics.optics)Physics - Optics
researchProduct

Polarization attraction using counter-propagating waves in optical fiber at telecommunication wavelengths

2008

International audience; In this work, we report the experimental observation of a polarization attraction process which can occur in optical fibers at telecommunication wavelengths. More precisely, we have numerically and experimentally shown that a polarization attractor, based on the injection of two counter-propagating waves around 1.55 mu m into a 2-m long high nonlinear fiber, can transform any input polarization state into a unique well-defined output polarization state.

Nonlinear opticsPhysics::OpticsPolarization-maintaining optical fiber02 engineering and technologyfibers01 natural sciencesNonlinear optical devices010309 optics020210 optoelectronics & photonicsOpticsPolarization0103 physical sciences0202 electrical engineering electronic engineering information engineeringFiber Optic TechnologyComputer SimulationOptical FibersCircular polarizationPhysics[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics][ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics]Polarization rotatorbusiness.industrySingle-mode optical fiberSignal Processing Computer-AssistedPolarization (waves)Optical FiberAtomic and Molecular Physics and OpticsNonlinear DynamicsCross-polarized wave generationPolarization mode dispersionTelecommunicationsOptical TelecommunicationbusinessTelecommunicationsPhotonic-crystal fiberOptics Express
researchProduct

Testing and extrapolating the nonlinear robustness of modulation formats

2005

The comparison of the robustness of modulation formats in fiber transmission systems facing nonlinear impairments and noise is carried out experimentally using a test link. Special techniques may be necessary when extrapolating by numerical simulations.

Nonlinear systemComputer simulationRobustness (computer science)Computer scienceQ factorFiber transmissionOptical communicationElectronic engineeringBit error rate
researchProduct

All-fiber based chaotic polarization scrambler

2014

We present a fiber-based polarization scrambler founded on the nonlinear interaction between a signal and its backward replica generated and amplified by a reflective loop. The output polarization dynamic turns out to be chaotic.

Nonlinear systemOpticsMaterials sciencePolarization rotatorComputer simulationbusiness.industryPolarization mode dispersionReplicaChaoticbusinessPolarization (waves)ScramblerAdvanced Photonics
researchProduct

Propagation pattern analysis during atrial fibrillation based on sparse modeling.

2012

In this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using si…

Normalization (statistics)Computer scienceAtrial fibrillation (AF)Biomedical EngineeringSignalPattern Recognition AutomatedElectrocardiographyelectrogramgroup least absolute selection and shrinkage operator (LASSO)Operator (computer programming)StatisticsAtrial FibrillationHumansComputer SimulationSelection (genetic algorithm)ShrinkageSignal processingNoise (signal processing)partial directed coherence (PDC)Models CardiovascularSignal Processing Computer-Assistedpropagation pattern analysiFrequency domainSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPattern recognition (psychology)AlgorithmAlgorithmsIEEE transactions on bio-medical engineering
researchProduct

Propagation pattern analysis during atrial fibrillation based on the adaptive group LASSO.

2012

The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.200.04 for LS estimatio…

Normalization (statistics)Computer scienceBiomedical EngineeringHealth InformaticsGroup lassoSensitivity and SpecificityPattern Recognition AutomatedHeart Conduction SystemStatisticsAtrial FibrillationCoherence (signal processing)AnimalsHumansComputer SimulationDiagnosis Computer-AssistedTime series1707ShrinkageSparse matrixPropagation patternModels CardiovascularReproducibility of ResultsElectroencephalographySignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaAlgorithmAlgorithmsAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
researchProduct

Optimal control design of preparation pulses for contrast optimization in MRI

2017

Abstract This work investigates the use of MRI radio-frequency (RF) pulses designed within the framework of optimal control theory for image contrast optimization. The magnetization evolution is modeled with Bloch equations, which defines a dynamic system that can be controlled via the application of the Pontryagin Maximum Principle (PMP). This framework allows the computation of optimal RF pulses that bring the magnetization to a given state to obtain the desired contrast after acquisition. Creating contrast through the optimal manipulation of Bloch equations is a new way of handling contrast in MRI, which can explore the theoretical limits of the system. Simulation experiments carried out…

Nuclear and High Energy PhysicsComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingComputationRF pulsesBiophysics010402 general chemistry01 natural sciencesBiochemistry030218 nuclear medicine & medical imaging03 medical and health sciencesMagnetizationMice0302 clinical medicineOpticsRobustness (computer science)Image Interpretation Computer-AssistedImage Processing Computer-AssistedAnimalsComputer SimulationGray MatterMuscle Skeletal[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imagingbusiness.industryPhantoms ImagingContrast (statistics)BrainReproducibility of ResultsContrastCondensed Matter PhysicsOptimal controlImage EnhancementBloch equationsMagnetic Resonance ImagingWhite Matter0104 chemical sciencesWeightingRatsOptimal control[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismOptimal control designBloch equations[ SPI.ELEC ] Engineering Sciences [physics]/ElectromagnetismFemalebusinessAlgorithmAlgorithms
researchProduct

Interaction position resolution simulations and in-beam measurements of the AGATA HPGe detectors

2011

WOS: 000290082600015

Nuclear and High Energy PhysicsFusion-evaporation ReactionsPhysics::Instrumentation and Detectorsg-ray trackingAstrophysics::High Energy Astrophysical PhenomenaMonte Carlo methodEvaporationRay tracking[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]01 natural sciencesParticle detectorNuclear physicsAGATA Fusion-evaporation reactions HPGe detectors Monte Carlo Simulation Ray tracking; Computer simulation Evaporation Monte Carlo methods Phase transitions; DetectorsHPGe Detectors0103 physical sciencesNuclear Experiment010306 general physicsInstrumentationGamma-ray TrackingPhysics010308 nuclear & particles physics4. EducationResolution (electron density)DetectorMonte Carlo SimulationMonte Carlo methodsDetectorsComputer simulationSemiconductor detectorPhase transitionsMonte Carlo SimulationsMeasuring instrumentHigh Energy Physics::ExperimentAGATAAGATABeam (structure)
researchProduct