Search results for "Invariant"

showing 10 items of 783 documents

Central polynomials and matrix invariants

1996

LetK be a field, charK=0 andM n (K) the algebra ofn×n matrices overK. If λ=(λ1,…,λ m ) andμ=(μ 1,…,μ m ) are partitions ofn 2 let $$\begin{gathered} F^{\lambda ,\mu } = \sum\limits_{\sigma ,\tau \in S_n 2} {\left( {\operatorname{sgn} \sigma \tau } \right)x_\sigma (1) \cdot \cdot \cdot x_\sigma (\lambda _1 )^{y_\tau } (1)^{ \cdot \cdot \cdot } y_\tau (\mu _1 )^{x\sigma } (\lambda _1 + 1)} \hfill \\ \cdot \cdot \cdot x_\sigma (\lambda _1 + \lambda _2 )^{y_\tau } (\mu _1 ^{ + 1} )^{ \cdot \cdot \cdot y_\tau } (\mu _1 + \mu _2 ) \hfill \\ \cdot \cdot \cdot x_\sigma (\lambda _1 + \cdot \cdot \cdot + \lambda _{\mu - 1} ^{ + 1} ) \hfill \\ \cdot \cdot \cdot x_\sigma (n^2 )^{y_\tau } (\mu _1 ^{ + \…

CombinatoricsPolynomialSymmetric groupGeneral MathematicsInvariants of tensorsField (mathematics)Algebra over a fieldLambdaMathematics
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On the exponential growth of graded Capelli polynomials

2013

In a free superalgebra over a field of characteristic zero we consider the graded Capelli polynomials Cap M+1[Y,X] and Cap L+1[Z,X] alternating on M+1 even variables and L+1 odd variables, respectively. Here we compute the superexponent of the variety of superalgebras determinated by Cap M+1[Y,X] and Cap L+1[Z,X]. An essential tool in our computation is the generalized-six-square theorem proved in [3].

CombinatoricsSettore MAT/02 - AlgebraExponential growthMathematics::Quantum AlgebraGeneral MathematicsZero (complex analysis)algebras with pilynomial identities noncommutative invariant theory asymptotic equivalenceField (mathematics)Algebra over a fieldVariety (universal algebra)Mathematics::Representation TheorySuperalgebraMathematicsIsrael Journal of Mathematics
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On the Efficiency of Affine Invariant Multivariate Rank Tests

1998

AbstractIn this paper the asymptotic Pitman efficiencies of the affine invariant multivariate analogues of the rank tests based on the generalized median of Oja are considered. Formulae for asymptotic relative efficiencies are found and, under multivariate normal and multivariatetdistributions, relative efficiencies with respect to Hotelling'sT2test are calculated.

CombinatoricsStatistics and ProbabilityMultivariate statisticsNumerical AnalysisRank (linear algebra)Consistent estimatorAffine invariantStatistics::MethodologyMultivariate normal distributionStatistics Probability and UncertaintyAsymptotic efficiency Oja median multivariate signed-rank test multivariate-rank test Pitman efficiencyMathematicsJournal of Multivariate Analysis
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The exact bounds for the degree of commutativity of a p-group of maximal class, I

2002

Abstract The first major study of p-groups of maximal class was made by Blackburn in 1958. He showed that an important invariant of these groups is the ‘degree of commutativity.’ Recently (1995) Fernandez-Alcober proved a best possible inequality for the degree of commutativity in terms of the order of the group. Recent computations for primes up to 43 show that sharper results can be obtained when an additional invariant is considered. A series of conjectures about this for all primes have been recorded in [A. Vera-Lopez et al., preprint]. In this paper, we prove two of these conjectures.

Combinatoricsp-groupClass (set theory)Pure mathematicsAlgebra and Number TheoryDegree (graph theory)Group (mathematics)Order (group theory)PreprintInvariant (mathematics)Commutative propertyMathematicsJournal of Algebra
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Approximated overlap error for the evaluation of feature descriptors on 3D scenes

2013

This paper presents a new framework to evaluate feature descriptors on 3D datasets. The proposed method employs the approximated overlap error in order to conform with the reference planar evaluation case of the Oxford dataset based on the overlap error. The method takes into account not only the keypoint centre but also the feature shape and it does not require complex data setups, depth maps or an accurate camera calibration. Only a ground-truth fundamental matrix should be computed, so that the dataset can be freely extended by adding further images. The proposed approach is robust to false positives occurring in the evaluation process, which do not introduce any relevant changes in the …

Complex data typeSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryComputer scienceGLOHEpipolar geometryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformPattern recognitionLIOPMROGHkeypoint descriptorSIFTepipolar geometryFalse positive paradoxComputer visionArtificial intelligencebusinessFundamental matrix (computer vision)descriptor evaluationCamera resectioning
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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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A modeling study suggesting how a reduction in the context-dependent input on CA1 pyramidal neurons could generate schizophrenic behavior.

2011

The neural mechanisms underlying schizophrenic behavior are unknown and very difficult to investigate experimentally, although a few experimental and modeling studies suggested possible causes for some of the typical psychotic symptoms related to this disease. The brain region most involved in these processes seems to be the hippocampus, because of its critical role in establishing memories for objects or events in the context in which they occur. In particular, a hypofunction of the N-methyl-D-aspartate (NMDA) component of the synaptic input on the distal dendrites of CA1 pyramidal neurons has been suggested to play an important role for the emergence of schizophrenic behavior. Modeling st…

Computer scienceCognitive Neurosciencemedia_common.quotation_subjectSchizophrenia Realistic model CA1 Hippocampus Object recognition Synaptic integrationCentral nervous systemModels NeurologicalCa1 neuronHippocampusHippocampal formationSynapse03 medical and health sciences0302 clinical medicineArtificial IntelligencePerceptionmedicineAnimalsHumansInvariant (mathematics)CA1 Region Hippocampal030304 developmental biologymedia_common0303 health sciencesRecallArtificial neural networkPyramidal NeuronSynaptic integrationPyramidal CellsCognitive neuroscience of visual object recognitionDendritesmedicine.diseasemedicine.anatomical_structurenervous systemSchizophreniaSynapsesSchizophreniaNMDA receptorNeuronNerve NetNeuroscience030217 neurology & neurosurgeryNeural networks : the official journal of the International Neural Network Society
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Quantitative evaluation of muscle synergy models: a single-trial task decoding approach.

2012

Delis, Ioannis | Berret, Bastien | Pozzo, Thierry | Panzeri, Stefano; International audience; ''Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements . Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies en codes task discriminating…

Computer scienceNeuroscience (miscellaneous)ORGANIZATIONMachine learningcomputer.software_genrelcsh:RC321-571Matrix decompositionNATURAL MOTOR BEHAVIORSFORCE03 medical and health sciencesCellular and Molecular NeurosciencePRIMITIVES0302 clinical medicinetask decodingmuscle synergiesMODULAR CONTROLMATRIX FACTORIZATIONOriginal Research ArticleMuscle activityInvariant (mathematics)Muscle synergylcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biologyARM MOVEMENTS0303 health sciencessingle-trial analysisarm movementbusiness.industryDimensionality reduction[SCCO.NEUR]Cognitive science/NeurosciencereachingTIME-VARYING SYNERGIES[ SCCO.NEUR ] Cognitive science/NeurosciencePATTERNS''NATURAL MOTOR BEHAVIORSArtificial intelligenceFORCE''Single trialSPINAL-CORDbusinesscomputer030217 neurology & neurosurgeryDecoding methodsNeuroscienceFrontiers in computational neuroscience
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Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests

2016

International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…

Computer scienceSparse codingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformImage processingDermoscopy02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHistogram0202 electrical engineering electronic engineering information engineeringmedicineComputer visionSegmentationMelanoma[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryMelanomaCancerPattern recognitionImage segmentationSparse approximationRandom forestsmedicine.diseaseClassificationRandom forest020201 artificial intelligence & image processingArtificial intelligenceSkin cancerNeural codingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Phase Fourier vector model for scale invariant three-dimensional image detection.

2009

A scale invariant 3D object detection method based on phase Fourier transform (PhFT) is addressed. Three-dimensionality is expressed in terms of range images. The PhFT of a range image gives information about the orientations of the surfaces in the 3D object. When the object is scaled, the PhFT becomes a distribution multiplied by a constant factor which is related to the scale factor. Then 3D scale invariant detection can be solved as illumination invariant detection process. Several correlation operations based on vector space representation are applied. Results show the tolerance of detection method to scale besides discrimination against false objects.

Computer sciencebusiness.industryImage detectionScale invarianceAtomic and Molecular Physics and OpticsObject detectionCorrelationConstant factorsymbols.namesakeOpticsFourier transformsymbolsVector space representationInvariant (mathematics)businessAlgorithmOptics express
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