Results 171 to 180 of about 15,675 (260)
Logarithmic Bloch spaces in the polydisc, endpoint results for Hankel operators and pointwise multipliers [PDF]
Benoît F. Sehba
openalex +1 more source
Pointwise Multipliers on the Morrey Spaces
A function g is called a pointwise multiplier from L^p〓to L^p〓, if the pointwise product fg belongs to L^p〓for each f∈L^p〓. We denote by PWM(L^p〓, Lp〓) the set of all pointwise multipliers from L^p〓to L^p〓. It is known that PWM(L^p〓, L^p〓)=L^p〓, 1/p〓+1/p〓=1/p〓. The purpose of this paper is to generalize the above equality to the Morrey spaces on spaces
openaire
Data‐Based Refinement of Parametric Uncertainty Descriptions
ABSTRACT We consider dynamical systems with a linear fractional representation involving parametric uncertainties which are either constant or varying with time. Given a finite‐horizon input‐state or input‐output trajectory of such a system, we propose a numerical scheme which iteratively improves the available knowledge about the involved constant ...
Tobias Holicki, Carsten W. Scherer
wiley +1 more source
Second-order asymptotics of fractional Gagliardo seminorms as s → 1 - and convergence of the associated gradient flows. [PDF]
Kubin A, Pagliari V, Tribuzio A.
europepmc +1 more source
Diabetic retinopathy detection based on mobile maxout network and weber local descriptor feature selection using retinal fundus image. [PDF]
Sheejakumari V +7 more
europepmc +1 more source
An Effective Physics‐Informed Neural Operator Framework for Predicting Wavefields
Abstract Solving the wave equation is fundamental for many geophysical applications. However, numerical solutions of the Helmholtz equation face significant computational and memory challenges. Therefore, we introduce a physics‐informed convolutional neural operator (CNO) (PICNO) to solve the Helmholtz equation efficiently.
X. Ma, T. Alkhalifah
wiley +1 more source
Comprehensive brain tumour concealment utilizing peak valley filtering and deeplab segmentation. [PDF]
Pradeep Kumar BP +3 more
europepmc +1 more source
Abstract This study focuses on the clustered landslide event triggered by intense rainfall on 16 June 2024 in the Fujian–Guangdong–Jiangxi border region, aiming to develop an efficient deep learning model for high‐accuracy landslide susceptibility mapping. Based on the mapped landslide distribution and insights from field investigations, we constructed
Senlin Luo +6 more
wiley +1 more source

