Results 21 to 30 of about 1,575,789 (284)

Fast Perturbative Algorithm Configurators [PDF]

open access: yes, 2020
Recent work has shown that the ParamRLS and ParamILS algorithm configurators can tune some simple randomised search heuristics for standard benchmark functions in linear expected time in the size of the parameter space. In this paper we prove a linear lower bound on the expected time to optimise any parameter tuning problem for ParamRLS, ParamILS as ...
Hall, G.T., Oliveto, P.S., Sudholt, D.
openaire   +3 more sources

Generating Fast Indulgent Algorithms [PDF]

open access: yesTheory of Computing Systems, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alistarh, D.   +3 more
openaire   +5 more sources

A Fast θ Scheme Combined with the Legendre Spectral Method for Solving a Fractional Klein–Gordon Equation

open access: yesFractal and Fractional, 2023
In the current work, a fast θ scheme combined with the Legendre spectral method was developed for solving a fractional Klein–Gordon equation (FKGE). The numerical scheme was provided by the Legendre spectral method in the spatial direction, and for the ...
Yanan Li   +3 more
doaj   +1 more source

A Fast Fractional Difference Algorithm [PDF]

open access: yesSSRN Electronic Journal, 2013
AbstractWe provide a fast algorithm for calculating the fractional difference of a time series. In standard implementations, the calculation speed (number of arithmetic operations) is of order T2, where T is the length of the time series. Our algorithm allows calculation speed of order TlogT.
Jensen, Andreas Noack   +1 more
openaire   +5 more sources

Robust and fast algorithm for extracting the periodic feature from jet engine modulation signals

open access: yesThe Journal of Engineering, 2019
Jet engine modulation (JEM), a modulation phenomenon induced by the rotating structure of jet engines, is a representative feature extracted from the radar returns for aircraft target recognition.
Jingming Sun, Junpeng Yu
doaj   +1 more source

Point Cloud Normal Estimation by Fast Guided Least Squares Representation

open access: yesIEEE Access, 2020
Normal estimation is an essential task for scanned point clouds in various CAD/CAM applications. The method (GLSRNE) based on guided least squares representation (GLSR) balances speed with quality well among state-of-the-art methods.
Jie Zhang   +4 more
doaj   +1 more source

Fast algorithm for Morphological Filters [PDF]

open access: yesJournal of Physics: Conference Series, 2011
In surface metrology, M-system (Mean-line filtering system) and E-system (Envelope filtering system) are two filtering approaches. Although M-system has been the dominant choice and played an important role in manufacturing control, Morphological filters, that evolved from the E-system, are believed to give better results in function prediction of ...
S. Lou, X. Jiang, P.J. Scott
openaire   +2 more sources

FAST—Fast Algorithm for the Scenario Technique

open access: yesOperations Research, 2014
The scenario approach is a recently introduced method to obtain feasible solutions to chance-constrained optimization problems based on random sampling. It has been noted that the sample complexity of the scenario approach rapidly increases with the number of optimization variables and this may pose a hurdle to its applicability to medium- and large ...
Caré, A., Garatti, S., CAMPI, Marco
openaire   +4 more sources

A Novel Technique for Robust and Fast Segmentation of Corneal Layer Interfaces Based on Spectral-Domain Optical Coherence Tomography Imaging

open access: yesIEEE Access, 2017
A novel approach to segment corneal layer interfaces using optical coherence tomography images is presented. In this paper, we performed customized edge detection for initial location of interfaces, fitting the initial interfaces to circles via ...
Tianqiao Zhang   +6 more
doaj   +1 more source

An Extended Reweighted 1 Minimization Algorithm for Image Restoration

open access: yesMathematics, 2021
This paper proposes an effective extended reweighted ℓ1 minimization algorithm (ERMA) to solve the basis pursuit problem minu∈Rn{||u||1:Au=f} in compressed sensing, where A∈Rm×n, m≪n.
Sining Huang, Yupeng Chen, Tiantian Qiao
doaj   +1 more source

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