Search results for "SPECTRA"

showing 10 items of 3542 documents

Supernova 1987A: a Template to Link Supernovae to their Remnants

2015

The emission of supernova remnants reflects the properties of both the progenitor supernovae and the surrounding environment. The complex morphology of the remnants, however, hampers the disentanglement of the two contributions. Here we aim at identifying the imprint of SN 1987A on the X-ray emission of its remnant and at constraining the structure of the environment surrounding the supernova. We performed high-resolution hydrodynamic simulations describing SN 1987A soon after the core-collapse and the following three-dimensional expansion of its remnant between days 1 and 15000 after the supernova. We demonstrated that the physical model reproducing the main observables of SN 1987A during …

Shock wavesupernovae: individual (SN 1987A)Astrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsPower lawSpectral lineGravitational collapseAstrophysics::Solar and Stellar AstrophysicsHydrodynamics instabilities ISM: supernova remnants shock waves supernovae: individual (SN 1987A) X-rays: ISM.EjectaAstrophysics::Galaxy AstrophysicsISM: supernova remnantsHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsNebulaAstronomy and AstrophysicsObservableshock wavesX-rays: ISMhydrodynamics instabilities ISM: supernova remnants shock waves supernovae: individual: SN 1987A X-rays: ISMSupernovainstabilitiesSpace and Planetary ScienceHydrodynamicsAstrophysics - High Energy Astrophysical Phenomena
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Rapid parameter determination of discrete damped sinusoidal oscillations

2020

We present different computational approaches for the rapid extraction of the signal parameters of discretely sampled damped sinusoidal signals. We compare time- and frequency-domain-based computational approaches in terms of their accuracy and precision and computational time required in estimating the frequencies of such signals, and observe a general trade-off between precision and speed. Our motivation is precise and rapid analysis of damped sinusoidal signals as these become relevant in view of the recent experimental developments in cavity-enhanced polarimetry and ellipsometry, where the relevant time scales and frequencies are typically within the ∼1 − 10 µs and ∼1 − 100 MHz ranges, …

Signal Processing (eess.SP)Accuracy and precisionPhysics - Instrumentation and DetectorsAcousticsPolarimetryFOS: Physical sciences02 engineering and technologyApplied Physics (physics.app-ph)01 natural sciencesSignal010309 opticssymbols.namesakeOptics0103 physical sciencesFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingPhysicsbusiness.industrySpectral densityInstrumentation and Detectors (physics.ins-det)Physics - Applied Physics021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsMicrosecondFourier transformsymbols0210 nano-technologybusinessMatrix methodOptics (physics.optics)Physics - Optics
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Deep Completion Autoencoders for Radio Map Estimation

2022

Radio maps provide metrics such as power spectral density for every location in a geographic area and find numerous applications such as UAV communications, interference control, spectrum management, resource allocation, and network planning to name a few. Radio maps are constructed from measurements collected by spectrum sensors distributed across space. Since radio maps are complicated functions of the spatial coordinates due to the nature of electromagnetic wave propagation, model-free approaches are strongly motivated. Nevertheless, all existing schemes for radio occupancy map estimation rely on interpolation algorithms unable to learn from experience. In contrast, this paper proposes a…

Signal Processing (eess.SP)Computer scienceApplied MathematicsSpectral densityInterference (wave propagation)computer.software_genreAutoencoderSpectrum managementComputer Science ApplicationsNetwork planning and designSpatial reference systemFOS: Electrical engineering electronic engineering information engineeringResource allocationData miningElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal ProcessingcomputerInterpolation
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Statistical Learning for End-to-End Simulations

2018

End-to-end mission performance simulators (E2ES) are suitable tools to accelerate satellite mission development from concet to deployment. One core element of these E2ES is the generation of synthetic scenes that are observed by the various instruments of an Earth Observation mission. The generation of these scenes rely on Radiative Transfer Models (RTM) for the simulation of light interaction with the Earth surface and atmosphere. However, the execution of advanced RTMs is impractical due to their large computation burden. Classical interpolation and statistical emulation methods of pre-computed Look-Up Tables (LUT) are therefore common practice to generate synthetic scenes in a reasonable…

Signal Processing (eess.SP)Earth observation010504 meteorology & atmospheric sciencesComputer science0211 other engineering and technologiesFOS: Physical sciences02 engineering and technologyLinear interpolation01 natural sciencesSpectral lineComputational sciencesymbols.namesakeSampling (signal processing)Radiative transferFOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal ProcessingGaussian processInstrumentation and Methods for Astrophysics (astro-ph.IM)021101 geological & geomatics engineering0105 earth and related environmental sciencesEmulationGround-penetrating radarLookup tableRadiancesymbolsAstrophysics - Instrumentation and Methods for AstrophysicsInterpolation
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Multi-temporal and Multi-source Remote Sensing Image Classification by Nonlinear Relative Normalization

2016

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corres…

Signal Processing (eess.SP)FOS: Computer and information sciences010504 meteorology & atmospheric sciencesHyperspectral imagingComputer Vision and Pattern Recognition (cs.CV)0211 other engineering and technologiesNormalization (image processing)Computer Science - Computer Vision and Pattern Recognition02 engineering and technology3107 Atomic and Molecular Physics and Optics01 natural sciencesLaboratory of Geo-information Science and Remote SensingComputer vision910 Geography & travelMathematicsDomain adaptationContextual image classificationImage and Video Processing (eess.IV)1903 Computers in Earth SciencesPE&RCClassificationAtomic and Molecular Physics and OpticsComputer Science ApplicationsKernel method10122 Institute of GeographyKernel (image processing)Feature extractionFeature extractionVery high resolutionGraph-based methods1706 Computer Science ApplicationsFOS: Electrical engineering electronic engineering information engineeringLaboratorium voor Geo-informatiekunde en Remote SensingComputers in Earth SciencesElectrical Engineering and Systems Science - Signal ProcessingEngineering (miscellaneous)021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingManifold alignmentbusiness.industryNonlinear dimensionality reductionHistogram matchingKernel methodsPattern recognitionElectrical Engineering and Systems Science - Image and Video ProcessingManifold learningArtificial intelligence2201 Engineering (miscellaneous)businessISPRS Journal of Photogrammetry and Remote Sensing
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Interpolation and Gap Filling of Landsat Reflectance Time Series

2018

Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particular allow to combine different multiresolution datasets. We present here an optimal interpolation approach to generate smoothed and gap-free time series of Landsat reflectance data. We fuse MODIS (moderate-resolution imaging spectroradiometer) and Landsat data globally using the Google Earth Engine (GEE) platform. The optimal interpolator exploits GEE ability to ingest large amounts of data (Landsat climatologies) and uses simple linear operations that scale easily in the cloud. The approach shows very good result…

Signal Processing (eess.SP)Image fusion010504 meteorology & atmospheric sciencesComputer scienceMultispectral image0211 other engineering and technologies02 engineering and technology01 natural sciencesReflectivitySpectroradiometerFOS: Electrical engineering electronic engineering information engineeringTime seriesElectrical Engineering and Systems Science - Signal ProcessingScale (map)Image resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInterpolationDownscaling
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Data-Driven Spectrum Cartography via Deep Completion Autoencoders

2019

Spectrum maps, which provide RF spectrum metrics such as power spectral density for every location in a geographic area, find numerous applications in wireless communications such as interference control, spectrum management, resource allocation, and network planning to name a few. Spectrum cartography techniques construct these maps from a collection of measurements collected by spatially distributed sensors. Due to the nature of the propagation of electromagnetic waves, spectrum maps are complicated functions of the spatial coordinates. For this reason, model-free approaches have been preferred. However, all existing schemes rely on some interpolation algorithm unable to learn from data. …

Signal Processing (eess.SP)Network architectureComputer sciencebusiness.industry05 social sciencesSpectral density050801 communication & media studiesSpectrum managementNetwork planning and design0508 media and communicationsSpatial reference system0502 economics and businessFOS: Electrical engineering electronic engineering information engineeringResource allocationWireless050211 marketingElectrical Engineering and Systems Science - Signal ProcessingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550CartographyInterpolation
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Iterative Reconstruction of Signals on Graph

2020

We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or better performance both in terms of convergence rate and computational efficiency.

Signal Processing (eess.SP)signal processing algorithmIterative methodComputer science02 engineering and technologyIterative reconstructionSettore MAT/08 - Analisi NumericaSettore MAT/05 - Analisi Matematica0202 electrical engineering electronic engineering information engineeringFOS: MathematicsFOS: Electrical engineering electronic engineering information engineeringsignal reconstructionMathematics - Numerical AnalysisElectrical and Electronic EngineeringElectrical Engineering and Systems Science - Signal ProcessingSignal reconstructionApplied Mathematics020206 networking & telecommunicationsNumerical Analysis (math.NA)Graphspectral analysisGraph theoryRate of convergenceSignal ProcessingGraph (abstract data type)Algorithmsignal processing algorithmsInterpolation
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Improving the performance of acousto-optic tunable filters in imaging applications

2010

Acousto-optic tunable filters (AOTFs) can be used as spectral filters for the implementation of multispectral imaging systems. However, obtaining quality images is challenging. In this work, we propose several improvements that enable the use of these systems in quantitative spectroscopic imaging applications. The improvements are based on three pillars: 1. a finer spectral bandpass shaping by dynamically optimizing the radio frequency (rf) driving signal, 2. an extensive calibration process, and 3. careful image preprocessing that uses calibration data to correct some well known AOTF issues in imaging applications. A novel multispectral imaging instrument is built using commercial off-the-…

Signal generatorComputer sciencebusiness.industryMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingSignalAtomic and Molecular Physics and OpticsComputer Science ApplicationsBand-pass filterElectronic engineeringComputer visionArtificial intelligenceRadio frequencyElectrical and Electronic EngineeringbusinessOptical filterImage resolutionJournal of Electronic Imaging
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Configurable Passband Imaging Spectrometer Based on Acousto-optic Tunable Filter

2008

This work presents a new configurable imaging spectrometer called Autonomous Tunable Filtering System (ATFS). The system can be configured to acquire a single narrow spectral band, a composite multispectral image, or a broad pass-band. This flexibility is given by the use of an Acousto-Optic Tunable Filter (AOTF) driven by a programmable radio frequency (rf) signal generator. The AOTF acts as a light-diffraction element which output wavelength is selected by the frequency of an rf signal applied to it. The designed rf driver is based on a high-speed Digital-to-Analog converter, which can synthesize any composite rf waveform formed by a combination of sine signals. The images are formed thro…

Signal generatorbusiness.product_categoryComputer sciencebusiness.industryMultispectral imageImaging spectrometerPhysics::OpticsFilter (signal processing)OpticsWaveformRadio frequencyArtificial intelligencebusinessPassbandDigital camera
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