Results 81 to 90 of about 4,491 (232)
Incomplete q-Chebyshev polynomials
In this paper, we get the generating functions of the q-Chebyshev polynomials using ?z operator, which is ?z (f(z))= f(qz) for any given function f (z). Also considering explicit formulas of the q-Chebyshev polynomials, we give new generalizations of the q-Chebyshev polynomials called the incomplete q-Chebyshev polynomials of the first and ...
Cetin, Mirac, Ercan, Elif, TUĞLU, NAİM
openaire +5 more sources
The image is supposed to evoke particle swarm optimization applied to Bi–Pt bimetallic nanoparticles. Each bird represents a candidate nanoparticle structure. The lake and its shorelines represent the potential energy surface, generated using the ChiMES physics‐informed machine learning potential.
Raphaël Vangheluwe +6 more
wiley +1 more source
A New Identity Involving the Chebyshev Polynomials
In this paper, firstly, we introduced a second order non-linear recursive sequence, then we use this sequence and the combinatorial methods to perform a deep study on the computational problem concerning one kind sums, which includes the Chebyshev ...
Yixue Zhang, Zhuoyu Chen
doaj +1 more source
On the Polynomial Multiplication in Chebyshev Form
We give an efficient multiplication method for polynomials in Chebyshev form. This multiplication method is different from the previous ones. Theoretically, we show that the number of multiplications is at least as good as Karatsuba-based algorithm. Moreover, using the proposed method, we improve the number of additions slightly.
Akleylek, Sedat +2 more
openaire +4 more sources
ABSTRACT The study of nanofluids has attracted significant attention due to their superior thermophysical properties, making them ideal for thermal transport in engineering and biomedical applications. Motivated by these capabilities, this study develops a novel three‐dimensional mathematical model for electrically conducting Sutterby nanofluids ...
A. M. Obalalu +4 more
wiley +1 more source
Determinants of Tridiagonal and Circulant Matrices Special Form by Chebyshev Polynomials
Along with the development of science, many researchers have found new methods to determine the determinant of a matrix of more than three orders.
Nurliantika Nurliantika +2 more
doaj +1 more source
On Polynomial Multiplication in Chebyshev Basis [PDF]
In a recent paper Lima, Panario and Wang have provided a new method to multiply polynomials in Chebyshev basis which aims at reducing the total number of multiplication when polynomials have small degree. Their idea is to use Karatsuba's multiplication scheme to improve upon the naive method but without being able to get rid of its quadratic complexity.
openaire +4 more sources
Rician Likelihood Loss for Quantitative MRI With Self‐Supervised Deep Learning
We introduce a numerically accurate and stable negative log Rician (NLR) likelihood loss for quantitative MR imaging with self‐supervised deep learning. Self‐supervised neural networks trained with the NLR loss have reduced bias in intra‐voxel incoherent motion diffusion coefficient at low signal‐to‐noise ratio (SNR) compared to the traditional mean ...
Christopher S. Parker +5 more
wiley +1 more source
The Chebyshev polynomial of best approximation to a given function on an interval [PDF]
Oved Shisha
openalex +2 more sources
Average‐Case Matrix Discrepancy: Satisfiability Bounds
ABSTRACT Given a sequence of d×d$$ d\times d $$ symmetric matrices {Wi}i=1n$$ {\left\{{\mathbf{W}}_i\right\}}_{i=1}^n $$, and a margin Δ>0$$ \Delta >0 $$, we investigate whether it is possible to find signs (ε1,…,εn)∈{±1}n$$ \left({\varepsilon}_1,\dots, {\varepsilon}_n\right)\in {\left\{\pm 1\right\}}^n $$ such that the operator norm of the signed sum ...
Antoine Maillard
wiley +1 more source

