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Estimation of the Discrete-Time Fourier Transform (DTFT) at points of a finite domain arises in many imaging applications. A new approach to this task, the Golden Angle Linogram Fourier Domain (GALFD), is presented, together with a…

Hypergeometric functions and their generalizations play an important r\^{o}les in diverse applications. Many authors have been established generalizations of hypergeometric functions by a number ways. In this paper, we aim at establishing…

Classical Analysis and ODEs · Mathematics 2017-05-18 Praveen Agarwal , Mohamed Jleli

Standard sparse pseudo-input approximations to the Gaussian process (GP) cannot handle complex functions well. Sparse spectrum alternatives attempt to answer this but are known to over-fit. We suggest the use of variational inference for…

Machine Learning · Statistics 2015-03-23 Yarin Gal , Richard Turner

Gaussian Markov random fields (GMRFs) are probabilistic graphical models widely used in spatial statistics and related fields to model dependencies over spatial structures. We establish a formal connection between GMRFs and convolutional…

Machine Learning · Statistics 2020-08-11 Per Sidén , Fredrik Lindsten

Nonlocal QFT of one-component scalar field $\varphi$ in $D$-dimensional Euclidean spacetime is considered. The generating functional (GF) of complete Green functions $\mathcal{Z}$ as a functional of external source $j$, coupling constant…

High Energy Physics - Theory · Physics 2019-08-30 M. Bernard , V. A. Guskov , M. G. Ivanov , A. E. Kalugin , S. L. Ogarkov

Graph signal processing (GSP) leverages the inherent signal structure within graphs to extract high-dimensional data without relying on translation invariance. It has emerged as a crucial tool across multiple fields, including learning and…

General Mathematics · Mathematics 2025-02-21 Yu Zhang , Bing-Zhao Li

In classic graph signal processing, given a real-valued graph signal, its graph Fourier transform is typically defined as the series of inner products between the signal and each eigenvector of the graph Laplacian. Unfortunately, this…

Machine Learning · Computer Science 2022-01-12 Fanchao Meng , Mark Orr , Samarth Swarup

We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral…

Numerical Analysis · Mathematics 2012-07-17 Erwan Faou , Fabio Nobile , Christophe Vuillot

We construct a calculus for generalized $\mathbf{SG}$ Fourier integral operators, extending known results to a broader class of symbols of $\mathbf{SG}$ type. In particular, we do not require that the phase functions are homogeneous. We…

Functional Analysis · Mathematics 2020-03-03 S. Coriasco , J. Toft

We propose a multi-dimensional (M-D) sparse Fourier transform inspired by the idea of the Fourier projection-slice theorem, called FPS-SFT. FPS-SFT extracts samples along lines (1-dimensional slices from an M-D data cube), which are…

Signal Processing · Electrical Eng. & Systems 2017-12-01 Shaogang Wang , Vishal M. Patel , Athina Petropulu

Cross-modal metric learning is a prominent research topic that bridges the semantic heterogeneity between vision and language. Existing methods frequently utilize simple cosine or complex distance metrics to transform the pairwise features…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Haiwen Diao , Ying Zhang , Shang Gao , Jiawen Zhu , Long Chen , Huchuan Lu

Generic approximation of entire functions by their Pad\'{e} approximants has been achieved in the past (\cite{3}). In the present article we obtain generic approximation of holomorphic functions on arbitrary open sets by sequences of their…

Complex Variables · Mathematics 2011-06-02 G. Fournodavlos , V. Nestoridis

We compute bilinear integrals involving Macdonald and Gegenbauer functions. These integrals are convergent only for a limited range of parameters. However, when one uses generalized integrals they can be computed essentially without…

Classical Analysis and ODEs · Mathematics 2023-06-16 Jan Dereziński , Christian Gaß , Błażej Ruba

In this paper we talk about the so-called SuperMathematics Functions (SMF), which often constiture the base for generating technical neo-geometrical objects.

General Mathematics · Mathematics 2009-03-10 Mircea Eugen Selariu , Marian Nitu , Florentin Smarandache

We study the properties of different type of transforms by means of operational methods and discuss the relevant interplay with many families of special functions. We consider in particular the binomial transform and its generalizations. A…

Mathematical Physics · Physics 2010-10-11 G. Dattoli , E. Sabia

Let $(M,g)$ be a smooth, compact, Riemannian manifold and $\{\phi_h\}$ a sequence of $L^2$-normalized Laplace eigenfunctions on $M$. For a smooth submanifold $H\subset M$, we consider the growth of the restricted eigenfunctions $\phi_h|_H$…

Analysis of PDEs · Mathematics 2022-04-06 Madelyne M. Brown

Developing explicit pseudorandom generators (PRGs) for prominent categories of Boolean functions is a key focus in computational complexity theory. In this paper, we investigate the PRGs against the functions of degree-$d$ polynomial…

Computational Complexity · Computer Science 2025-04-22 Penghui Yao , Mingnan Zhao

Gaussian random fields (GRFs) constitute an important part of spatial modelling, but can be computationally infeasible for general covariance structures. An efficient approach is to specify GRFs via stochastic partial differential equations…

Methodology · Statistics 2016-08-11 Geir-Arne Fuglstad , Finn Lindgren , Daniel Simpson , Håvard Rue

The single-particle Green's function (GF) of mesoscopic structures plays a central role in mesoscopic quantum transport. The recursive GF technique is a standard tool to compute this quantity numerically, but it lacks physical transparency…

Mesoscale and Nanoscale Physics · Physics 2017-02-22 Shu-Hui Zhang , Wen Yang , Kai Chang

Using the existence of infinite numbers $k$ in the non-Archimedean ring of Robinson-Colombeau, we define the hyperfinite Fourier transform (HFT) by considering integration extended to $[-k,k]^{n}$ instead of $(-\infty,\infty)^{n}$. In order…

Functional Analysis · Mathematics 2022-10-03 Akbarali Mukhammadiev , Diksha Tiwari , Paolo Giordano
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