Search results for "kernel"

Lipschitz continuity of Cheeger-harmonic functions in metric measure spaces

2003

Abstract We use the heat equation to establish the Lipschitz continuity of Cheeger-harmonic functions in certain metric spaces. The metric spaces under consideration are those that are endowed with a doubling measure supporting a (1,2)-Poincare inequality and in addition supporting a corresponding Sobolev–Poincare-type inequality for the modification of the measure obtained via the heat kernel. Examples are given to illustrate the necessity of our assumptions on these spaces. We also provide an example to show that in the general setting the best possible regularity for the Cheeger-harmonic functions is Lipschitz continuity.

Fractional integration, differentiation, and weighted Bergman spaces

1999

We study the action of fractional differentiation and integration on weighted Bergman spaces and also the Taylor coeffficients of functions in certain subclasses of these spaces. We then derive several criteria for the multipliers between such spaces, complementing and extending various recent results. Univalent Bergman functions are also considered.

Some Inclusion Theorems for Orlicz and Musielak-Orlicz Type Spaces

1995

where K is a homogeneous kernel and f belongs to some KSthe functional space. In these papers the estimates are taken with respect to the KSthe norm of the space. Recently in [2] we obtained analogous estimates for functions belonging to Orlicz or Musielak-Orlicz type spaces L ~, with respect to the canonical modular functional. These results enable us to say that, for example,

Riemann-Hilbert approach to the time-dependent generalized sine kernel

2011

We derive the leading asymptotic behavior and build a new series representation for the Fredholm determinant of integrable integral operators appearing in the representation of the time and distance dependent correlation functions of integrable models described by a six-vertex R-matrix. This series representation opens a systematic way for the computation of the long-time, long-distance asymptotic expansion for the correlation functions of the aforementioned integrable models away from their free fermion point. Our method builds on a Riemann–Hilbert based analysis.

Analytic Bergman operators in the semiclassical limit

2018

Transposing the Berezin quantization into the setting of analytic microlocal analysis, we construct approximate semiclassical Bergman projections on weighted $L^2$ spaces with analytic weights, and show that their kernel functions admit an asymptotic expansion in the class of analytic symbols. As a corollary, we obtain new estimates for asymptotic expansions of the Bergman kernel on $\mathbb{C}^n$ and for high powers of ample holomorphic line bundles over compact complex manifolds.

Existence and multiplicity results for semilinear elliptic Dirichlet problems in exterior domains

1995

Generation of stimulus features for analysis of FMRI during natural auditory experiences

2014

In contrast to block and event-related designs for fMRI experiments, it becomes much more difficult to extract events of interest in the complex continuous stimulus for finding corresponding blood-oxygen-level dependent (BOLD) responses. Recently, in a free music listening fMRI experiment, acoustic features of the naturalistic music stimulus were first extracted, and then principal component analysis (PCA) was applied to select the features of interest acting as the stimulus sequences. For feature generation, kernel PCA has shown its superiority over PCA in various applications, since it can implicitly exploit nonlinear relationship among features and such relationship seems to exist genera…

Solving the NLO BK equation in coordinate space

2016

We present results from a numerical solution of the next-to-leading order (NLO) BalitskyKovchegov (BK) equation in coordinate space in the large Nc limit. We show that the solution is not stable for initial conditions that are close to those used in phenomenological applications of the leading order equation. We identify the problematic terms in the NLO kernel as being related to large logarithms of a small parent dipole size, and also show that rewriting the equation in terms of the “conformal dipole” does not remove the problem. Our results qualitatively agree with expectations based on the behavior of the linear NLO BFKL equation.

Generalization of Canny–Deriche filter for detection of noisy exponential edge

2002

This paper presents a generalization of the Canny-Deriche filter for ramp edge detection with optimization criteria used by Canny (signal-to-noise ratio, localization, and suppression of false responses). Using techniques similar to those developed by Deriche, we derive a filter which maximizes the product of the first two criteria under the constraint of the last one. The result is an infinite length impulse response filter which leads to a stable third-order recursive implementation. Its performance shows an increase of the signal-to-noise ratio in the case of blurred and noisy images, compared to the results obtained from Deriche's filter.

A kernel regression approach to cloud and shadow detection in multitemporal images

2013

Earth observation satellites will provide in the next years time series with enough revisit time allowing a better surface monitoring. In this work, we propose a cloud screening and a cloud shadow detection method based on detecting abrupt changes in the temporal domain. It is considered that the time series follows smooth variations and abrupt changes in certain spectral features will be mainly due to the presence of clouds or cloud shadows. The method is based on linear and nonlinear regression analysis; in particular we focus on the regularized least squares and kernel regression methods. Experiments are carried out using Landsat 5 TM time series acquired over Albacete (Spain), and compa…