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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

We present an introduction to fractal interpolation beginning with a global set-up and then extending to a local, a non-stationary, and finally the novel quaternionic setting. Emphasis is placed on the overall perspective with references…

Functional Analysis · Mathematics 2021-09-01 Peter R Massopust

It is often useful to perform integration over learned functions represented by neural networks. However, this integration is usually performed numerically, as analytical integration over learned functions (especially neural networks) is…

Machine Learning · Computer Science 2023-12-27 Ryan Kortvelesy

The fractional Fourier transform (FrFT), a fundamental operation in physics that corresponds to a rotation of phase space by any angle, is also an indispensable tool employed in digital signal processing for noise reduction. Processing of…

Fractal geometry deals mainly with irregularity and captures the complexity of a structure or phenomenon. In this article, we focus on the approximation of set-valued functions using modern machinery on the subject of fractal geometry. We…

Functional Analysis · Mathematics 2025-09-23 Parneet Kaur , Rattan Lal , Ankit Kumar , Saurabh Verma

A laboratory prototype spectral/spatial interferometer has been constructed to demonstrate the feasibility of the double Fourier technique at Far Infrared (FIR) wavelengths (0.15 - 1 THz). It is planned to use this demonstrator to…

Instrumentation and Methods for Astrophysics · Physics 2015-06-04 William F. Grainger , Roser Juanola-Parramon , Peter A. R. Ade , Matt Griffin , Flo Liggins , Enzo Pascale , Giorgio Savini , Bruce Swinyard

The Cambrian explosion of easily accessible pre-trained diffusion models suggests a demand for methods that combine multiple different pre-trained diffusion models without incurring the significant computational burden of re-training a…

Machine Learning · Computer Science 2025-03-04 Marta Skreta , Lazar Atanackovic , Avishek Joey Bose , Alexander Tong , Kirill Neklyudov

Consider a sparse multivariate polynomial f with integer coefficients. Assume that f is represented as a "modular black box polynomial", e.g. via an algorithm to evaluate f at arbitrary integer points, modulo arbitrary positive integers.…

Symbolic Computation · Computer Science 2024-01-01 Joris van der Hoeven , Grégoire Lecerf

Fourier transforms are ubiquitous mathematical tools in basic and applied sciences. We here report classical and quantum optical realizations of the discrete fractional Fourier transform, a generalization of the Fourier transform. In the…

In this paper, we introduce Partial Information Decomposition of Features (PIDF), a new paradigm for simultaneous data interpretability and feature selection. Contrary to traditional methods that assign a single importance value, our…

Machine Learning · Computer Science 2025-11-17 Charles Westphal , Stephen Hailes , Mirco Musolesi

Existing digital sensors capture images at fixed spatial and spectral resolutions (e.g., RGB, multispectral, and hyperspectral images), and each combination requires bespoke machine learning models. Neural Implicit Functions partially…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Gengchen Mai , Ni Lao , Weiwei Sun , Yuchi Ma , Jiaming Song , Chenlin Meng , Hongxu Ma , Jinmeng Rao , Ziyuan Li , Stefano Ermon

The graph Fourier transform (GFT) is a fundamental tool in graph signal processing and has recently been extended to the graph fractional Fourier transform (GFRFT). Existing sampling methods in the GFRFT domain are primarily designed to…

General Mathematics · Mathematics 2026-05-27 Yu Zhang , Jia-Yin Peng , Bing-Zhao Li

This paper proposes a two-view deterministic geometric model fitting method, termed Superpixel-based Deterministic Fitting (SDF), for multiple-structure data. SDF starts from superpixel segmentation, which effectively captures prior…

Computer Vision and Pattern Recognition · Computer Science 2016-07-21 Guobao Xiao , Hanzi Wang , Yan Yan , David Suter

Speckles arise when coherent light interacts with biological tissues. Information retrieval from speckles is desired yet challenging, requiring understanding or mapping of the multiple scattering process, or reliable capability to reverse…

Image and Video Processing · Electrical Eng. & Systems 2020-05-05 Huanhao Li , Zhipeng Yu , Yunqi Luo , Shengfu Cheng , Lihong V. Wang , Yuanjin Zheng , Puxiang Lai

Let $f$ be a $r\times m$-matrix of holomorphic functions that is generically surjective. We provide explicit integral representation of holomorphic $\psi$ such that $\phi=f\psi$, provided that $\phi$ is holomorphic and annihilates a certain…

Complex Variables · Mathematics 2007-05-23 Mats Andersson

A method for 3D interpolation between hard spheres is described. The function to be interpolated could be the charge density between atoms in condensed matter. Its electrostatic potential is found analytically, and so are various integrals.…

Materials Science · Physics 2016-09-07 Yoshiro Nohara , O. K. Andersen

Mean value interpolation is a method for fitting a smooth function to piecewise-linear data prescribed on the boundary of a polygon of arbitrary shape, and has applications in computer graphics and curve and surface modelling. The method…

Numerical Analysis · Mathematics 2019-06-21 Michael S. Floater , Francesco Patrizi

In this article, we prove the following interpolation problem: if the composition of a function and a regular map between affine varieties is a regular function, then there exists a global regular function of the target variety that…

Algebraic Geometry · Mathematics 2023-02-20 Nilkantha Das

Fractal percolation exhibits a dramatic topological phase transition, changing abruptly from a dust-like set to a system spanning cluster. The transition points are unknown and difficult to estimate. In many classical percolation models the…

Probability · Mathematics 2026-01-14 Michael A. Klatt , Steffen Winter

In this paper we define an internal binary operation between functions called in the text \emph{fractal convolution}, that applies a pair of mappings into a fractal function. This is done by means of a suitable Iterated Function System. We…

Classical Analysis and ODEs · Mathematics 2019-07-16 M. A. Navascués , P. Massopust