The Experts below are selected from a list of 5256 Experts worldwide ranked by ideXlab platform
Jeanclaude Saut - One of the best experts on this subject based on the ideXlab platform.
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asymptotic integration of navier stokes equations with potential forces ii an explicit poincare dulac normal form
Journal of Functional Analysis, 2011Co-Authors: Ciprian Foias, Luan Hoang, Jeanclaude SautAbstract:Abstract We study the incompressible Navier–Stokes equations with potential body forces on the three-dimensional torus. We show that the Normalization introduced in the paper [C. Foias, J.-C. Saut, Linearization and normal form of the Navier–Stokes equations with potential forces, Ann. Inst. H. Poincare Anal. Non Lineaire 4 (1) (1987) 1–47], produces a Poincare–Dulac normal form which is obtained by an explicit change of variable. This change is the formal power series expansion of the inverse of the Normalization Map. Each homogeneous term of a finite degree in the series is proved to be well-defined in appropriate Sobolev spaces and is estimated recursively by using a family of homogeneous gauges which is suitable for estimating homogeneous polynomials in infinite dimensional spaces.
Ciprian Foias - One of the best experts on this subject based on the ideXlab platform.
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asymptotic integration of navier stokes equations with potential forces ii an explicit poincare dulac normal form
Journal of Functional Analysis, 2011Co-Authors: Ciprian Foias, Luan Hoang, Jeanclaude SautAbstract:Abstract We study the incompressible Navier–Stokes equations with potential body forces on the three-dimensional torus. We show that the Normalization introduced in the paper [C. Foias, J.-C. Saut, Linearization and normal form of the Navier–Stokes equations with potential forces, Ann. Inst. H. Poincare Anal. Non Lineaire 4 (1) (1987) 1–47], produces a Poincare–Dulac normal form which is obtained by an explicit change of variable. This change is the formal power series expansion of the inverse of the Normalization Map. Each homogeneous term of a finite degree in the series is proved to be well-defined in appropriate Sobolev spaces and is estimated recursively by using a family of homogeneous gauges which is suitable for estimating homogeneous polynomials in infinite dimensional spaces.
Luan Hoang - One of the best experts on this subject based on the ideXlab platform.
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asymptotic integration of navier stokes equations with potential forces ii an explicit poincare dulac normal form
Journal of Functional Analysis, 2011Co-Authors: Ciprian Foias, Luan Hoang, Jeanclaude SautAbstract:Abstract We study the incompressible Navier–Stokes equations with potential body forces on the three-dimensional torus. We show that the Normalization introduced in the paper [C. Foias, J.-C. Saut, Linearization and normal form of the Navier–Stokes equations with potential forces, Ann. Inst. H. Poincare Anal. Non Lineaire 4 (1) (1987) 1–47], produces a Poincare–Dulac normal form which is obtained by an explicit change of variable. This change is the formal power series expansion of the inverse of the Normalization Map. Each homogeneous term of a finite degree in the series is proved to be well-defined in appropriate Sobolev spaces and is estimated recursively by using a family of homogeneous gauges which is suitable for estimating homogeneous polynomials in infinite dimensional spaces.
Leslie Spencer - One of the best experts on this subject based on the ideXlab platform.
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The endoscopic fundamental lemma for unitary Friedberg-Jacquet periods
2020Co-Authors: Leslie SpencerAbstract:We prove the endoscopic fundamental lemma for the Lie algebra of the symmetric space $U(2n)/U(n)\times U(n)$, where $U(n)$ denotes a unitary group of rank $n$. This is the first major step in the stabilization of the relative trace formula associated to the $U(n)\times U(n)$-periods of automorphic forms on $U(2n)$.Comment: 62 pages. Comments welcome! v2: Several typos fixed; error in Normalization Map of Hecke algebras in Section 3.2 fixe
Michael Blumenstein - One of the best experts on this subject based on the ideXlab platform.
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texture based feature mining for crowd density estimation a study
Image and Vision Computing New Zealand, 2016Co-Authors: Muhammad Saqib, Sultan Daud Khan, Michael BlumensteinAbstract:Texture feature is an important feature descriptor for many image analysis applications. The objectives of this research are to determine distinctive texture features for crowd density estimation and counting. In this paper, we have comprehensively reviewed different texture features and their different possible combinations to evaluate their performance on pedestrian crowds. A two-stage classification and regression based framework have been proposed for performance evaluation of all the texture features for crowd density estimation and counting. According to the framework, input images are divided into blocks and blocks into cells of different sizes, having varying crowd density levels. Due to perspective distortion, people appearing close to the camera contribute more to the feature vector than people far away. Therefore, features extracted are normalized using a perspective Normalization Map of the scene. At the first stage, image blocks are classified using multi-class SVM into different density level. At the second stage Gaussian Process Regression is used to re gress low-level features to count. Various texture features and their possible combinations are evaluated on publicly available dataset.
