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A Radial Basis Function Generated Finite-Differences (RBF-FD) inspired technique for evaluating definite integrals over bounded volumes that have smooth boundaries in three dimensions is described. A key aspect of this approach is that it…

Numerical Analysis · Mathematics 2023-01-11 Jonah A. Reeger

This paper presents the construction of a hidden variable fractal interpolation function using Edelstein contractions in an iterated function system based on a finite collection of data points. The approach incorporates an iterated function…

Dynamical Systems · Mathematics 2026-01-23 Aiswarya T , Srijanani Anurag Prasad

For fixed natural numbers $r$ and $s$, where $2\leq s \leq r$, we consider a representation of numbers from the interval $[0;\frac{r}{s-1}]$ obtained by encoding numbers by means of the alphabet $A=\{0,1,...,r\}$ via the expansion…

Number Theory · Mathematics 2026-01-27 M. V. Pratsiovytyi , S. P. Ratushniak , Yu. Yu. Vovk , Ya. V. Goncharenko

This article presents the construction of a non-affine hypersurface on an $n$-simplex in $\mathbb{R}^n$. Additionally, fractal dimension of the graph of a non-affine multivariate real-valued fractal function is estimated under certain…

Dynamical Systems · Mathematics 2024-11-14 A. Hossain , J. Buescu

Fractal sets, by definition, are non-differentiable, however their dimension can be continuous, differentiable, and arithmetically manipulable as function of their construction parameters. A new arithmetic for fractal dimension of polyadic…

Metric Geometry · Mathematics 2009-10-28 Francisco R. Villatoro

The fractal and self-similarity properties are revealed in many real complex networks. However, the classical information dimension of complex networks is not practical for real complex networks. In this paper, a new information dimension…

Social and Information Networks · Computer Science 2015-06-17 Daijun Wei , Bo Wei , Yong Hu , Haixin Zhang , Yong Deng

We develop a versatile framework which allows us to rigorously estimate the Hausdorff dimension of maximal conformal graph directed Markov systems in $\mathbb{R}^n$ for $n \geq 2$. Our method is based on piecewise linear approximations of…

Dynamical Systems · Mathematics 2025-05-01 Vasileios Chousionis , Dmitriy Leykekhman , Mariusz Urbański , Erik Wendt

We perform fractal analysis on a closed classical hard-wall billiard, the circular billiard with a straight cut, assuming there are two openings on the boundary. We use a two-dimensional set of initial conditions that produce all possible…

Chaotic Dynamics · Physics 2012-04-27 Suhan Ree

We introduce two frameworks in order to deal with fractal and multi-fractal analysis for subset sum problems where some embedding into the $1$-dimensional Euclidean space plays an important role. As one of these frameworks, the notion of…

Combinatorics · Mathematics 2020-08-24 Shoichi Kamada

We evaluate the shattering dimension of various classes of linear functionals on various symmetric convex sets. The proofs here relay mostly on methods from the local theory of normed spaces and include volume estimates, factorization…

Probability · Mathematics 2007-05-23 Shahar Mendelson , Gideon Schechtman

Boxicity of a graph $G(V,$ $E)$, denoted by $box(G)$, is the minimum integer $k$ such that $G$ can be represented as the intersection graph of axis parallel boxes in $\mathbb{R}^k$. The problem of computing boxicity is inapproximable even…

Data Structures and Algorithms · Computer Science 2014-03-06 Abhijin Adiga , Jasine Babu , L. Sunil Chandran

Building upon [1], this study aims to introduce fractal geometry into graph theory, and to establish a potential theoretical foundation for complex networks. Specifically, we employ the method of substitution to create and explore…

Dynamical Systems · Mathematics 2024-05-29 Nero Ziyu Li

We use persistent homology in order to define a family of fractal dimensions, denoted $\mathrm{dim}_{\mathrm{PH}}^i(\mu)$ for each homological dimension $i\ge 0$, assigned to a probability measure $\mu$ on a metric space. The case of…

This work is an analytical and numerical study of the composition of several fractals into one and of the relation between the composite dimension and the dimensions of the component fractals. In the case of composition of standard IFS with…

Metric Geometry · Mathematics 2020-10-20 Yann Lanoiselee , Laurent Nivanen , Aziz El Kaabouchi , Qiuping A. Wang

For a hyperbolic map f on a saddle type fractal Lambda with self-intersections, the number of f- preimages of a point x in Lambda may depend on x. This makes estimates of the stable dimensions more difficult than for diffeomorphisms or for…

Dynamical Systems · Mathematics 2013-01-10 Eugen Mihailescu , Bernd Stratmann

We study numerical computation of conformal invariants of domains in the complex plane. In particular, we provide an algorithm for computing the conformal capacity of a condenser. The algorithm applies for wide kind of geometries: domains…

Complex Variables · Mathematics 2020-08-19 Mohamed M S Nasser , Matti Vuorinen

We study the spectrum of the Fibonacci Hamiltonian and prove upper and lower bounds for its fractal dimension in the large coupling regime. These bounds show that as $\lambda \to \infty$, $\dim (\sigma(H_\lambda)) \cdot \log \lambda$…

Mathematical Physics · Physics 2014-12-30 David Damanik , Mark Embree , Anton Gorodetski , Serguei Tcheremchantsev

The fractal dimension curves of urban form and growth fall into two categories: One can be described by common logistic function, and the other can be described with quadratic logistic function. The approach to estimating the parameter of…

Physics and Society · Physics 2025-08-28 Yanguang Chen

We design a Quasi-Polynomial time deterministic approximation algorithm for computing the integral of a multi-dimensional separable function, supported by some underlying hyper-graph structure, appropriately defined. Equivalently, our…

Data Structures and Algorithms · Computer Science 2024-02-14 David Gamarnik , Devin Smedira

Developing a robust generalization measure for the performance of machine learning models is an important and challenging task. A lot of recent research in the area focuses on the model decision boundary when predicting generalization. In…

Machine Learning · Computer Science 2020-12-24 Valeri Alexiev
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