Results 21 to 30 of about 302,091 (291)

ON THE CONVERGENCE OF THE LEAST SQUARE METHOD IN CASE OF NON-UNIFORM GRIDS

open access: yesПроблемы анализа, 2019
Let f(t) be a continuous on [−1, 1] function, which values are given at the points of arbitrary non-uniform grid ΩN = = {tj} N−1 j=0 , where nodes tj satisfy the only condition ηj 6tj 6ηj+1, 0 6 j 6 N − 1, and nodes ηj are such that −1 = η0 < η1 < η2
M. S. Sultanakhmedov
doaj   +1 more source

METHODS OF APPROXIMATION OF FUNCTIONS BY GENERALIZED POLYNOMIALS IN NUMERICAL ANALYSIS PROBLEMS RELATED TO CALCULATIONS ON APPROXIMATE DATA

open access: yesНаука. Инновации. Технологии, 2022
Introduction: the methods of representation of functions given approximately by their singular integrals in relation to approximation problems and numerical methods for solving boundary value problems for differential equations are Investigated.
Igor Eduardovich Naats   +2 more
doaj  

A Deep-Network Piecewise Linear Approximation Formula

open access: yesIEEE Access, 2021
The mathematical foundation of deep learning is the theorem that any continuous function can be approximated within any specified accuracy by using a neural network with certain non-linear activation functions. However, this theorem does not tell us what
Gengsheng L. Zeng
doaj   +1 more source

Taylor Polynomials in a High Arithmetic Precision as Universal Approximators

open access: yesComputation
Function approximation is a fundamental process in a variety of problems in computational mechanics, structural engineering, as well as other domains that require the precise approximation of a phenomenon with an analytic function. This work demonstrates
Nikolaos Bakas
doaj   +1 more source

AN ENHANCED DIFFERENTIAL EVOLUTION ALGORITHM WITH ADAPTIVE WEIGHT BOUNDS FOR EFFICIENT TRAINING OF NEURAL NETWORKS

open access: yesInformatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2023
Artificial neural networks are essential intelligent tools for various learning tasks. Training them is challenging due to the nature of the data set, many training weights, and their dependency, which gives rise to a complicated high-dimensional error ...
Saithip Limtrakul   +1 more
doaj   +1 more source

The Principle of Localization at the Class of Functions Integrable in the Riemann for the Processes of Lagrange - Sturm - Liouville [PDF]

open access: yesИзвестия Саратовского университета. Новая серия: Математика. Механика. Информатика, 2020
Let us say that the principle of localization holds at the class of functions $F$ at point $x_0 \in [0, \pi]$ for the Lagrange\,--\,Sturm\,--\,Liouville interpolation process $L_n^{SL}(f,x)$ if $\lim_{n \rightarrow \infty}\left|L_n^{SL}(f, x_0)-L_n^{SL ...
Aleksandr Yurievich Trynin   +1 more
doaj   +1 more source

Dual Taylor Series, Spline Based Function and Integral Approximation and Applications

open access: yesMathematical and Computational Applications, 2019
In this paper, function approximation is utilized to establish functional series approximations to integrals. The starting point is the definition of a dual Taylor series, which is a natural extension of a Taylor series, and spline based series ...
Roy M. Howard
doaj   +1 more source

Personalizing the Pediatric Hematology/Oncology Fellowship: Adapting Training for the Next Generation

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT The pediatric hematology‐oncology fellowship training curriculum has not substantially changed since its inception. The first year of training is clinically focused, and the second and third years are devoted to scholarship. However, this current structure leaves many fellows less competitive in the current job market, resulting in ...
Scott C. Borinstein   +3 more
wiley   +1 more source

Random vector functional link networks for function approximation on manifolds

open access: yesFrontiers in Applied Mathematics and Statistics
The learning speed of feed-forward neural networks is notoriously slow and has presented a bottleneck in deep learning applications for several decades. For instance, gradient-based learning algorithms, which are used extensively to train neural networks,
Deanna Needell   +4 more
doaj   +1 more source

Development of a numerical method for solving optimization problems approximation of the function given approximately and its derivatives based on the variational approach

open access: yesНаука. Инновации. Технологии, 2022
Introduction: the presented work continues the authors' research on the methods of the theory of approximation of functions of a real variable, given approximately, on the basis of their representation by integrals. Materials and methods of research: the
Igor Naats   +2 more
doaj  

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