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Numerical Computation, Approximation of Functions and Applied Mathematics II
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Numerical Computation, Approximation of Functions and Applied Mathematics II

A special issue of Axioms (ISSN 2075-1680). This special issue belongs to the section "Mathematical Analysis".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 1577

Special Issue Editor

Prof. Dr. Peixin Ye

E-Mail Website
Guest Editor
School of Mathematical Sciences and LPMC, Nankai University, Tianjin 300071, China
Interests: approximation theory and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A basic and important problem in numerical computation is the need to resolve complicated functions into simpler, easier-to-compute functions. Good numerical methods based on the theory of the approximation of functions have many applications in numerous branches of applied mathematics, such as computer-aided geometric design, machine learning, and signal processing. The primary purpose of this Special Issue is to highlight the recent progress made in the theory and application of function approximation. Topics may include, but are not limited to, the following: multivariate approximation, numerical integration, optimization, machine learning, signal processing, and computer-aided geometric design.

Prof. Dr. Peixin Ye
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Axioms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • approximation of functions
  • numerical computation
  • computational complexity
  • optimization
  • machine learning
  • signal processing

Related Special Issue

Published Papers (3 papers)

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Research

17 pages, 916 KiB  
Article
Sparse Signal Recovery via Rescaled Matching Pursuit
by Wan Li and Peixin Ye
Axioms 2024, 13(5), 288; https://doi.org/10.3390/axioms13050288 - 24 Apr 2024
Viewed by 215
Abstract
We propose the Rescaled Matching Pursuit (RMP) algorithm to recover sparse signals in high-dimensional Euclidean spaces. The RMP algorithm has less computational complexity than other greedy-type algorithms, such as Orthogonal Matching Pursuit (OMP). We show that if the restricted isometry property is satisfied, [...] Read more.
We propose the Rescaled Matching Pursuit (RMP) algorithm to recover sparse signals in high-dimensional Euclidean spaces. The RMP algorithm has less computational complexity than other greedy-type algorithms, such as Orthogonal Matching Pursuit (OMP). We show that if the restricted isometry property is satisfied, then the upper bound of the error between the original signal and its approximation can be derived. Furthermore, we prove that the RMP algorithm can find the correct support of sparse signals from random measurements with a high probability. Our numerical experiments also verify this conclusion and show that RMP is stable with the noise. So, the RMP algorithm is a suitable method for recovering sparse signals. Full article
(This article belongs to the Special Issue Numerical Computation, Approximation of Functions and Applied Mathematics II)
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18 pages, 382 KiB  
Article
On the Convergence of an Approximation Scheme of Fractional-Step Type, Associated to a Nonlinear Second-Order System with Coupled In-Homogeneous Dynamic Boundary Conditions
by Constantin Fetecău, Costică Moroşanu and Silviu-Dumitru Pavăl
Axioms 2024, 13(5), 286; https://doi.org/10.3390/axioms13050286 - 23 Apr 2024
Viewed by 191
Abstract
The paper concerns a nonlinear second-order system of coupled PDEs, having the principal part in divergence form and subject to in-homogeneous dynamic boundary conditions, for both θ(t,x) and φ(t,x). Two main topics [...] Read more.
The paper concerns a nonlinear second-order system of coupled PDEs, having the principal part in divergence form and subject to in-homogeneous dynamic boundary conditions, for both θ(t,x) and φ(t,x). Two main topics are addressed here, as follows. First, under a certain hypothesis on the input data, f1, f2, w1, w2, α, ξ, θ0, α0, φ0, and ξ0, we prove the well-posedness of a solution θ,α,φ,ξ, which is θ(t,x),α(t,x)∈Wp1,2(Q)×Wp1,2(Σ), φ(t,x),ξ(t,x)∈Wν1,2(Q)×Wp1,2(Σ), ν=min{q,μ}. According to the new formulation of the problem, we extend the previous results, allowing the new mathematical model to be even more complete to describe the diversity of physical phenomena to which it can be applied: interface problems, image analysis, epidemics, etc. The main goal of the present paper is to develop an iterative scheme of fractional-step type in order to approximate the unique solution to the nonlinear second-order system. The convergence result is established for the new numerical method, and on the basis of this approach, a conceptual algorithm, alg-frac_sec-ord_u+varphi_dbc, is elaborated. The benefit brought by such a method consists of simplifying the computations so that the time required to approximate the solutions decreases significantly. Some conclusions are given as well as new research topics for the future. Full article
(This article belongs to the Special Issue Numerical Computation, Approximation of Functions and Applied Mathematics II)
16 pages, 896 KiB  
Article
Vector-Valued Shepard Processes: Approximation with Summability
by Oktay Duman and Biancamaria Della Vecchia
Axioms 2023, 12(12), 1124; https://doi.org/10.3390/axioms12121124 - 15 Dec 2023
Cited by 1 | Viewed by 814
Abstract
In this work, vector-valued continuous functions are approximated uniformly on the unit hypercube by Shepard operators. If λ denotes the usual parameter of the Shepard operators and m is the dimension of the hypercube, then our results show that it is possible to [...] Read more.
In this work, vector-valued continuous functions are approximated uniformly on the unit hypercube by Shepard operators. If λ denotes the usual parameter of the Shepard operators and m is the dimension of the hypercube, then our results show that it is possible to obtain a uniform approximation of a continuous vector-valued function by these operators when λ≥m+1. By using three-dimensional parametric plots, we illustrate this uniform approximation for some vector-valued functions. Finally, the influence in approximation by regular summability processes is studied, and their motivation is shown. Full article
(This article belongs to the Special Issue Numerical Computation, Approximation of Functions and Applied Mathematics II)
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