Results 21 to 30 of about 170,844 (265)

ABOUT WAVELET-BASED COMPUTATIONAL BEAM ANALYSIS WITH THE USE OF DAUBECHIES SCALING FUNCTIONS

open access: yesInternational Journal for Computational Civil and Structural Engineering, 2019
The first part of the distinctive paper contains brief review of wavelet-based numerical and semianalytical analysis, particularly with the use of Daubechies scaling functions.
Marina Mozgaleva   +2 more
doaj   +1 more source

Scaling-invariant Functions versus Positively Homogeneous Functions [PDF]

open access: yesJournal of Optimization Theory and Applications, 2021
Scaling-invariant functions preserve the order of points when the points are scaled by the same positive scalar (with respect to a unique reference point). Composites of strictly monotonic functions with positively homogeneous functions are scaling-invariant with respect to zero.
Touré, Cheikh   +3 more
openaire   +5 more sources

Ising model with varying spin strength on a scale-free network: scaling functions and critical amplitude ratios

open access: yesCondensed Matter Physics
Recently, a novel model to describe ordering in systems comprising agents which, although matching in their binarity (i.e., maintaining the iconic Ising features of “+” or “–”, “up” or “down”, “yes” or “no”), still differing in their strength was ...
M. Krasnytska
doaj   +1 more source

Scaling Laws for Partially Developed Turbulence

open access: yesFrontiers in Applied Mathematics and Statistics, 2022
We formulate multifractal models for velocity differences and gradients which describe the full range of length scales in turbulent flow, namely: laminar, dissipation, inertial, and stirring ranges.
Abigail Hsu, Ryan Kaufman, James Glimm
doaj   +1 more source

The generalised scaling function: A note [PDF]

open access: yesNuclear Physics B, 2010
A method for determining the generalised scaling function(s) arising in the high spin behaviour of long operator anomalous dimensions in the planar $sl(2)$ sector of ${\cal N}=4$ SYM is proposed. The all-order perturbative expansion around the strong coupling is detailed for the prototypical third and fourth scaling functions, showing the emergence of ...
D. FIORAVANTI, P. GRINZA, ROSSI, Marco
openaire   +2 more sources

On the Approximate Solution of Partial Integro-Differential Equations Using the Pseudospectral Method Based on Chebyshev Cardinal Functions

open access: yesMathematics, 2021
In this paper, we apply the pseudospectral method based on the Chebyshev cardinal function to solve the parabolic partial integro-differential equations (PIDEs).
Fairouz Tchier   +3 more
doaj   +1 more source

Scaling functions robust to translations [PDF]

open access: yesIEEE Transactions on Signal Processing, 1998
Summary: The discrete wavelet transform (DWT) is popular in a wide variety of applications. Its sparse sampling eliminates redundancy in the representation of signals and leads to efficient processing. However, the DWT lacks translation invariance. This makes it ill suited for many problems where the received signal is the superposition of arbitrarily ...
Steven A. Benno, José M. F. Moura
openaire   +1 more source

Quantum quench and scaling of entanglement entropy

open access: yesPhysics Letters B, 2017
Global quantum quench with a finite quench rate which crosses critical points is known to lead to universal scaling of correlation functions as functions of the quench rate.
Paweł Caputa   +3 more
doaj   +1 more source

Universality of Abelian and non-Abelian Wannier functions in generalized one-dimensional Aubry-André-Harper models

open access: yesPhysical Review Research, 2021
Within a Dirac model in 1+1 dimensions, a prototypical model to describe low-energy physics for a wide class of lattice models, we propose a field-theoretical version for the representation of Wannier functions, the Zak-Berry connection, and the ...
Kiryl Piasotski   +5 more
doaj   +1 more source

Scaling Up Influence Functions

open access: yesProceedings of the AAAI Conference on Artificial Intelligence, 2022
We address efficient calculation of influence functions for tracking predictions back to the training data. We propose and analyze a new approach to speeding up the inverse Hessian calculation based on Arnoldi iteration. With this improvement, we achieve, to the best of our knowledge, the first successful implementation of influence functions that ...
Andrea Schioppa   +3 more
openaire   +2 more sources

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