Search results for "SPECTRA"

showing 10 items of 3542 documents

Appearances of pseudo-bosons from Black-Scholes equation

2016

It is a well known fact that the Black-Scholes equation admits an alternative representation as a Schr\"odinger equation expressed in terms of a non self-adjoint hamiltonian. We show how {\em pseudo-bosons}, linear or not, naturally arise in this context, and how they can be used in the computation of the pricing kernel.

ComputationFOS: Physical sciencesStatistical and Nonlinear PhysicsBlack–Scholes modelMathematical Physics (math-ph)Mathematics::Spectral Theory01 natural sciences010305 fluids & plasmasSchrödinger equationsymbols.namesakeStochastic discount factor0103 physical sciencessymbols010306 general physicsHamiltonian (quantum mechanics)Settore MAT/07 - Fisica MatematicaMathematical PhysicsStatistical and Nonlinear PhysicBosonMathematical physicsMathematics
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Theoretical studies of isomers of C 3 H 2 using a multiconfigurational approach

2000

The C3H2 isomers are important molecules in interstellar space. An understanding of their electronic structure can contribute significantly to the interpretation of interstellar spectra. In a theoretical study of the C3H2 isomers a multiconfigurational treatment is of interest because many of the isomers are carbenes or diradicals. We present such an investigation of all possible C3H2 isomers. The most important features of their electronic and vibrational spectra are calculated. Earlier theoretical studies are reviewed and it is shown that the present study yields the same order of stability for the singlet and triplet states as most previous studies.

Computational chemistryChemistryPhysics::Atomic and Molecular ClustersMoleculeElectronic structureSinglet statePhysics::Chemical PhysicsPhysical and Theoretical ChemistryAstrophysics::Galaxy AstrophysicsSpectral lineVibrational spectraTheoretical Chemistry Accounts: Theory, Computation, and Modeling (Theoretica Chimica Acta)
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A Variational Approach for Denoising Hyperspectral Images Corrupted by Poisson Distributed Noise

2014

Poisson distributed noise, such as photon noise is an important noise source in multi- and hyperspectral images. We propose a variational based denoising approach, that accounts the vectorial structure of a spectral image cube, as well as the poisson distributed noise. For this aim, we extend an approach for monochromatic images, by a regularisation term, that is spectrally and spatially adaptive and preserves edges. In order to take the high computational complexity into account, we derive a Split Bregman optimisation for the proposed model. The results show the advantages of the proposed approach compared to a marginal approach on synthetic and real data.

Computational complexity theorybusiness.industryNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHyperspectral imagingPoisson distributionTerm (time)symbols.namesakeNoiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceMonochromatic colorCubebusinessAlgorithmMathematics
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Acoustic spectral hole-burning in a two-level system ensemble

2020

AbstractMicroscopic two-level system (TLS) defects at dielectric surfaces and interfaces are among the dominant sources of loss in superconducting quantum circuits, and their properties have been extensively probed using superconducting resonators and qubits. We report on spectroscopy of TLSs coupling to the strain field in a surface acoustic wave (SAW) resonator. The narrow free spectral range of the resonator allows for two-tone spectroscopy where a strong pump is applied at one resonance, while a weak signal is used to probe a different mode. We map the spectral hole burnt by the pump tone as a function of frequency and extract parameters of the TLS ensemble. Our results suggest that det…

Computer Networks and CommunicationsQC1-999FOS: Physical sciences02 engineering and technologyDielectric01 natural sciencesMolecular physicsResonator0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)Computer Science (miscellaneous)Coherence (signal processing)010306 general physicsSpectroscopyPhysicsQuantum PhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsPhysicsSurface acoustic waveResonanceStatistical and Nonlinear PhysicsQA75.5-76.95021001 nanoscience & nanotechnologyComputational Theory and MathematicsElectronic computers. Computer scienceSpectral hole burning0210 nano-technologyQuantum Physics (quant-ph)Free spectral range
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Homology of pseudodifferential operators on manifolds with fibered cusps

2003

The Hochschild homology of the algebra of pseudodifferential operators on a manifold with fibered cusps, introduced by Mazzeo and Melrose, is studied and computed using the approach of Brylinski and Getzler. One of the main technical tools is a new convergence criterion for tri-filtered half-plane spectral sequences. Using trace-like functionals that generate the 0 0 -dimensional Hochschild cohomology groups, the index of a fully elliptic fibered cusp operator is expressed as the sum of a local contribution of Atiyah-Singer type and a global term on the boundary. We announce a result relating this boundary term to the adiabatic limit of the eta invariant in a particular case.

Computer Science::Machine LearningHochschild homologyApplied MathematicsGeneral MathematicsFibered knotHomology (mathematics)Computer Science::Digital LibrariesCohomologyManifoldAlgebraStatistics::Machine LearningElliptic operatorEta invariantMathematics::K-Theory and HomologySpectral sequenceComputer Science::Mathematical SoftwareMathematicsTransactions of the American Mathematical Society
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Learning spatial filters for multispectral image segmentation.

2010

International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.

Computer Science::Machine LearningMultispectral image0211 other engineering and technologies02 engineering and technology01 natural sciencesRegularization (mathematics)010104 statistics & probability[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]Life ScienceComputer visionSegmentation0101 mathematicsLarge margin method021101 geological & geomatics engineeringMathematicsImage segmentationContextual image classificationPixelbusiness.industryPattern recognitionImage segmentationSupport vector machineComputingMethodologies_PATTERNRECOGNITIONmultispectral imageSpatial FilteringArtificial intelligenceGradient descentbusiness
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Extension of luminance component based demosaicking algorithm to 4- and 5-band multispectral images

2021

Abstract Multispectral imaging systems are currently expanding with a variety of multispectral demosaicking algorithms. But these algorithms have limitations due to the remarkable presence of artifacts in the reconstructed image. In this paper, we propose a powerful multispectral image demosaicking method that focuses on the G band and luminance component. We've first identified a relevant 4-and 5-band multispectral filter array (MSFA) with the dominant G band and then proposed an algorithm that consistently estimates the missing G values and other missing components using a convolution operator and a weighted bilinear interpolation algorithm based on the luminance component. Using the cons…

Computer engineering. Computer hardwareDemosaicingDemosaicking algorithmComputer scienceMultispectral imageBilinear interpolationQA75.5-76.95General MedicineExtension (predicate logic)Filter (signal processing)Multispectral filter arrayLuminanceConvolutionTK7885-7895G bandElectronic computers. Computer scienceComponent (UML)Weighted bilinear interpolationLuminance componentAlgorithmArray
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Spectrogram Analysis of Multipath Fading Channels under Variations of the Mobile Speed

2016

When modelling, analysing, and simulating mobile radio channels, it is generally assumed that the speed of the mobile station (MS) is constant. In practice, however, the mobile speed varies with time. Mobile speed variations result in nonwide- sense stationary multipath fading channels, which can be modelled by a sum-of-chirps (SOCh) processes. In this paper, we analyse the local Doppler power spectral density (PSD) of SOCh processes by using the concept of the spectrogram. The spectrogram provides an estimate of the local Doppler PSD and gives insight into how the Doppler PSD changes over time if the MS increases or decreases its speed. A closed-form solution is presented for the spectrogr…

Computer science010401 analytical chemistrySpectral density020206 networking & telecommunications02 engineering and technology01 natural sciences0104 chemical sciencesTime–frequency analysissymbols.namesakeMobile stationComputer Science::Networking and Internet Architecture0202 electrical engineering electronic engineering information engineeringsymbolsElectronic engineeringSpectrogramDoppler effectRandom variableMultipath propagationCommunication channel2016 IEEE 84th Vehicular Technology Conference (VTC-Fall)
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Sorting of Single Biomolecules based on Fourier Polar Representation of Surface Enhanced Raman Spectra

2016

AbstractSurface enhanced Raman scattering (SERS) spectroscopy becomes increasingly used in biosensors for its capacity to detect and identify single molecules. In practice, a large number of SERS spectra are acquired and reliable ranking methods are thus essential for analysing all these data. Supervised classification strategies, which are the most effective methods, are usually applied but they require pre-determined models or classes. In this work, we propose to sort SERS spectra in unknown groups with an alternative strategy called Fourier polar representation. This non-fitting method based on simple Fourier sine and cosine transforms produces a fast and graphical representation for sor…

Computer science02 engineering and technologyBiosensing Techniquescomputer.software_genreSpectrum Analysis Raman01 natural sciencesSpectral lineArticlesymbols.namesakeCysteineSpectroscopyRepresentation (mathematics)Sine and cosine transformsMultidisciplinary010401 analytical chemistrySortingModels Theoretical021001 nanoscience & nanotechnology0104 chemical sciencesFourier transformPrincipal component analysisOdorantssymbolsPolarData mining0210 nano-technologyRaman spectroscopyBiological systemcomputerMonte Carlo MethodRaman scatteringAlgorithmsScientific Reports
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Optimizing Kernel Ridge Regression for Remote Sensing Problems

2018

Kernel methods have been very successful in remote sensing problems because of their ability to deal with high dimensional non-linear data. However, they are computationally expensive to train when a large amount of samples are used. In this context, while the amount of available remote sensing data has constantly increased, the size of training sets in kernel methods is usually restricted to few thousand samples. In this work, we modified the kernel ridge regression (KRR) training procedure to deal with large scale datasets. In addition, the basis functions in the reproducing kernel Hilbert space are defined as parameters to be also optimized during the training process. This extends the n…

Computer science0211 other engineering and technologiesHyperspectral imagingContext (language use)Basis function02 engineering and technology01 natural sciencesData set010104 statistics & probabilityKernel (linear algebra)Kernel methodKernel (statistics)Radial basis function kernel0101 mathematics021101 geological & geomatics engineeringReproducing kernel Hilbert spaceRemote sensingIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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