Search results for "Smoothness"

showing 10 items of 43 documents

PIP-Spaces and Signal Processing

2009

Contemporary signal processing makes an extensive use of function spaces, always with the aim of getting a precise control on smoothness and decay properties of functions. In this chapter, we will discuss several classes of such function spaces that have found interesting applications, namely, mixed-norm spaces, amalgam spaces, modulation spaces, or Besov spaces. It turns out that all those spaces come in families indexed by one or more parameters, that specify, for instance, the local behavior or the asymptotic properties. In general, a single space, taken alone, does not have an intrinsic meaning, it is the family as a whole that does, which brings us to the very topic of this volume. In …

AlgebraModulation spaceSmoothnesssymbols.namesakeClass (set theory)Function spaceComputer scienceBergman spaceHilbert spacesymbolsBesov spaceSpace (mathematics)
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Error Bounds for the Numerical Evaluation of Integrals with Weights

1988

This paper is concerned with a procedure of obtaining error bounds for numerically evaluated integrals with weights. If \( - \infty \mathop < \limits_ = a < b\mathop < \limits_ = \infty \), w integrable over [a,b] and positive almost everywhere, then an approximation of \({I_W}f: = \int\limits_a^b {w\left( t \right)f\left( t \right)dt} \) by a quadrature rule \({Q_n}f: = \sum\limits_{i = 0}^n {{\alpha _i}f\left( {{t_i}} \right)} \) is leading to the error Enf ≔ Iwf ‒ Qnf. An algorithm is derived for the computation of bounds for |Enf| depending on the smoothness of the integrand f and on the degree of exactness of Q. As initial values this algorithm needs moments of the weighting function w…

Combinatoricssymbols.namesakeSmoothness (probability theory)Degree (graph theory)Simple (abstract algebra)StatisticssymbolsGaussian quadratureAlmost everywhereFunction (mathematics)Mathematics
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Uniformly nonsquare Banach spaces have the fixed point property for nonexpansive mappings

2006

Abstract It is shown that if the modulus Γ X of nearly uniform smoothness of a reflexive Banach space satisfies Γ X ′ ( 0 ) 1 , then every bounded closed convex subset of X has the fixed point property for nonexpansive mappings. In particular, uniformly nonsquare Banach spaces have this property since they are properly included in this class of spaces. This answers a long-standing question in the theory.

Discrete mathematicsMathematics::Functional AnalysisPure mathematicsUniformly nonsquare spacesApproximation propertyEberlein–Šmulian theoremBanach spaceNonexpansive mappingsUniformly convex spaceBanach manifoldFixed-point propertyNearly uniform smoothnessFixed pointsReflexive spaceLp spaceAnalysisMathematicsJournal of Functional Analysis
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On approximation of a class of stochastic integrals and interpolation

2004

Given a diffusion Y = (Y_{t})_{t \in [0,T]} we give different equivalent conditions so that a stochastic integral has an L 2-approximation rate of n −η, {\rm \eta \in (0,1/2],} if one approximates by integrals over piece-wise constant integrands where equidistant time nets of cardinality n + 1 are used. In particular, we obtain assertions in terms of smoothness properties of g(Y T ) in the sense of Malliavin calculus. After optimizing over non-equidistant time-nets of cardinality n + 1 in case {\rm \eta > 0} , it turns out that one always obtains a rate of n^{ - 1/2}, which is optimal. This applies to all functions g obtained in an appropriate way by the real interpolation method between th…

Discrete mathematicsSobolev spaceSmoothness (probability theory)CardinalityRate of convergenceEquidistantConstant (mathematics)Malliavin calculusInterpolationMathematicsStochastics and Stochastic Reports
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Tracking of Quantized Signals Based on Online Kernel Regression

2021

Kernel-based approaches have achieved noticeable success as non-parametric regression methods under the framework of stochastic optimization. However, most of the kernel-based methods in the literature are not suitable to track sequentially streamed quantized data samples from dynamic environments. This shortcoming occurs mainly for two reasons: first, their poor versatility in tracking variables that may change unpredictably over time, primarily because of their lack of flexibility when choosing a functional cost that best suits the associated regression problem; second, their indifference to the smoothness of the underlying physical signal generating those samples. This work introduces a …

Flexibility (engineering)SmoothnessComputer scienceSignal reconstructionKernel (statistics)Kernel regressionRegretStochastic optimizationAlgorithmRegression2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)
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On a Retarded Nonlocal Ordinary Differential System with Discrete Diffusion Modeling Life Tables

2021

In this paper, we consider a system of ordinary differential equations with non-local discrete diffusion and finite delay and with either a finite or an infinite number of equations. We prove several properties of solutions such as comparison, stability and symmetry. We create a numerical simulation showing that this model can be appropriate to model dynamical life tables in actuarial or demographic sciences. In this way, some indicators of goodness and smoothness are improved when comparing with classical techniques.

General Mathematicslattice dynamical systemslife tables010103 numerical & computational mathematics:CIENCIAS ECONÓMICAS [UNESCO]01 natural sciencesStability (probability)010104 statistics & probabilitydiscrete nonlocal diffusion problemsComputer Science (miscellaneous)Applied mathematics0101 mathematicsDiffusion (business)Engineering (miscellaneous)MathematicsDiffusion modelingSmoothness (probability theory)Computer simulationlcsh:MathematicsUNESCO::CIENCIAS ECONÓMICASlcsh:QA1-939Symmetry (physics)Ordinary differential systemordinary differential equationsOrdinary differential equationretarded equationsMathematics
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$n$-harmonic coordinates and the regularity of conformal mappings

2014

This article studies the smoothness of conformal mappings between two Riemannian manifolds whose metric tensors have limited regularity. We show that any bi-Lipschitz conformal mapping or $1$-quasiregular mapping between two manifolds with $C^r$ metric tensors ($r &gt; 1$) is a $C^{r+1}$ conformal (local) diffeomorphism. This result was proved in [12, 27, 33], but we give a new proof of this fact. The proof is based on $n$-harmonic coordinates, a generalization of the standard harmonic coordinates that is particularly suited to studying conformal mappings. We establish the existence of a $p$-harmonic coordinate system for $1 &lt; p &lt; \infty$ on any Riemannian manifold.

Harmonic coordinatesMathematics - Differential GeometryPure mathematicsSmoothness (probability theory)GeneralizationGeneral MathematicsCoordinate systemta111conformal mappingsConformal map53A30 (Primary) 35J60 35B65 (Secondary)Riemannian manifoldMathematics - Analysis of PDEsDifferential Geometry (math.DG)Metric (mathematics)FOS: MathematicsDiffeomorphismMathematics::Differential GeometryMathematicsAnalysis of PDEs (math.AP)
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Conformality and $Q$-harmonicity in sub-Riemannian manifolds

2016

We prove the equivalence of several natural notions of conformal maps between sub-Riemannian manifolds. Our main contribution is in the setting of those manifolds that support a suitable regularity theory for subelliptic $p$-Laplacian operators. For such manifolds we prove a Liouville-type theorem, i.e., 1-quasiconformal maps are smooth. In particular, we prove that contact manifolds support the suitable regularity. The main new technical tools are a sub-Riemannian version of p-harmonic coordinates and a technique of propagation of regularity from horizontal layers.

Harmonic coordinatesMathematics - Differential GeometryPure mathematicsWork (thermodynamics)morphism propertyGeneral Mathematicsconformal transformationBoundary (topology)Conformal map01 natural sciencesdifferentiaaligeometriaMathematics - Analysis of PDEsMathematics - Metric GeometryLiouville TheoremRegularity for p-harmonic functionSubelliptic PDE0103 physical sciencesFOS: MathematicsMathematics (all)0101 mathematicspopp measureMathematicsosittaisdifferentiaaliyhtälötsubelliptic PDESmoothnessQuasi-conformal mapApplied MathematicsHarmonic coordinates; Liouville Theorem; Quasi-conformal maps; Regularity for p-harmonic functions; Sub-Riemannian geometry; Subelliptic PDE; Mathematics (all); Applied Mathematicsta111Harmonic coordinate010102 general mathematics53C17 35H20 58C25Metric Geometry (math.MG)16. Peace & justiceregularity for p-harmonic functionsSub-Riemannian geometrysub-Riemannian geometryDifferential Geometry (math.DG)quasi-conformal mapsRegularity for p-harmonic functionsharmonic coordinates010307 mathematical physicsMathematics::Differential GeometrymonistotLiouville theoremAnalysis of PDEs (math.AP)
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SPECTRAL GEOMETRY OF SPACETIME

2000

Spacetime, understood as a globally hyperbolic manifold, may be characterized by spectral data using a 3+1 splitting into space and time, a description of space by spectral triples and by employing causal relationships, as proposed earlier. Here, it is proposed to use the Hadamard condition of quantum field theory as a smoothness principle.

High Energy Physics - TheoryPhysicsSmoothness (probability theory)Spacetime010308 nuclear & particles physics010102 general mathematicsMathematical analysisFOS: Physical sciencesSpectral geometryStatistical and Nonlinear Physics16. Peace & justiceCondensed Matter PhysicsSpace (mathematics)01 natural sciencesHigh Energy Physics - Theory (hep-th)Hadamard transform0103 physical sciencesGlobally hyperbolic manifold0101 mathematicsQuantum field theorySpectral dataInternational Journal of Modern Physics B
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Moving Averages for Market Timing

2016

This paper begins by presenting the moving average methodology of detecting the direction of a trend and identifying turning points in the trend in real time. The paper then proceeds to introduce the general weighted moving average, derives some of its key properties, and discusses how to quantitatively assess the two important characteristics of a moving average: the average lag time and the smoothness. Finally the paper aims to give an overview of some specific types of moving averages used in market timing. These types include regular moving averages, moving averages of moving averages, and mixed moving averages with less lag time. Different types of moving averages are compared to each …

Identification (information)Lag timeSmoothness (probability theory)Moving averageLagStatisticsEconometricsTurning pointMarket timingMoving average crossoverMathematicsSSRN Electronic Journal
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