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We developed fast direct solver for 3D Helmholtz and Maxwell equations in layered medium. The algorithm is based on the ideas of cyclic reduction for separable matrices. For the grids with major uniform part (within the survey domain in the…

Numerical Analysis · Mathematics 2019-09-04 Vladimir Druskin , Mikhail Zaslavsky

Hough transform is a popular low-level computer vision algorithm. Its computationally effective modification, Fast Hough transform (FHT), makes use of special subsets of image matrix to approximate geometric lines on it. Because of their…

Computer Vision and Pattern Recognition · Computer Science 2017-12-18 E. I. Ershov , S. M. Karpenko

The usage of linear transformations has great relevance for data decorrelation applications, like image and video compression. In that sense, the discrete Tchebichef transform (DTT) possesses useful coding and decorrelation properties. The…

Multimedia · Computer Science 2024-10-14 P. A. M. Oliveira , R. J. Cintra , F. M. Bayer , S. Kulasekera , A. Madanayake , V. A. Coutinho

We present an efficient algorithm for calculating spectral properties of large sparse Hamiltonian matrices such as densities of states and spectral functions. The combination of Chebyshev recursion and maximum entropy achieves high energy…

Condensed Matter · Physics 2009-10-30 R. N. Silver , H. Roder

We give two algebro-geometric inspired approaches to fast algorithms for Fourier transforms in algebraic signal processing theory based on polynomial algebras in several variables. One is based on module induction and one is based on a…

Numerical Analysis · Mathematics 2024-12-20 Bastian Seifert

This paper develops a constructive numerical scheme for Fourier-Bessel approximations on disks compatible with convolutions supported on disks. We address accurate finite Fourier-Bessel transforms (FFBT) and inverse finite Fourier-Bessel…

Numerical Analysis · Mathematics 2023-11-08 Arash Ghaani Farashahi , Gregory S. Chirikjian

Unions of graph Fourier multipliers are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators to the high-dimensional signals…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 David I Shuman , Pierre Vandergheynst , Pascal Frossard

The motivation of this paper is the development of an optimisation method for solving optimisation problems appearing in Chebyshev rational and generalised rational approximation problems, where the approximations are constructed as ratios…

Optimization and Control · Mathematics 2020-11-06 R. Díaz Millán , Nadezda Sukhorukova , Julien Ugon

Chebyshev Filtered Subspace Iteration (ChFSI) is widely used for computing a small subset of extremal eigenpairs from large matrices, particularly when the eigenpairs must be computed repeatedly as the system matrix evolves within an outer…

Computational Physics · Physics 2026-03-18 Nikhil Kodali , Kartick Ramakrishnan , Phani Motamarri

This is the second part in a series of papers on multi-step schemes for solving coupled forward backward stochastic differential equations (FBSDEs). We extend the basic idea in our former paper [W. Zhao, Y. Fu and T. Zhou, SIAM J. Sci.…

Numerical Analysis · Mathematics 2016-07-26 Yu Fu , Weidong Zhao , Tao Zhou

We analyze decay of Chebyshev coefficients and local Chebyshev approximations for functions of finite regularity on finite intervals, focusing on the framework where the interval length tends to zero while the number of approximation nodes…

Numerical Analysis · Mathematics 2025-09-19 Krishna Yamanappa Poojara , Sabhrant Sachan , Ambuj Pandey

We introduce and analyze a mesh-free two-level hybrid Chebyshev-Tucker tensor representation for approximating multivariate functions, which combines tensor-product Chebyshev interpolation with the low-rank Tucker decomposition of the…

Numerical Analysis · Mathematics 2026-05-19 Peter Benner , Boris N. Khoromskij , Venera Khoromskaia , Bonan Sun

Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite-dimensional functions from limited samples. This is a key task in computational science and engineering, e.g., surrogate modelling in…

Numerical Analysis · Mathematics 2023-11-08 Ben Adcock , Simone Brugiapaglia , Nick Dexter , Sebastian Moraga

Existing fast algorithms for bilateral and nonlocal means filtering mostly work with grayscale images. They cannot easily be extended to high-dimensional data such as color and hyperspectral images, patch-based data, flow-fields, etc. In…

Computer Vision and Pattern Recognition · Computer Science 2018-11-07 Pravin Nair , Kunal. N. Chaudhury

Peridynamics is a nonlocal generalization of continuum mechanics theory which adresses discontinuous problems without using partial derivatives and replacing its by an integral operator. As a consequence, it finds applications in the…

Numerical Analysis · Mathematics 2022-09-07 Luciano Lopez , Sabrina Francesca Pellegrino

The Fast Fourier Transform (FFT) is an algorithm of paramount importance in signal processing as it allows to apply the Fourier transform in O(n log n) instead of O(n 2) arithmetic operations. Graph Signal Processing (GSP) is a recent…

Numerical Analysis · Computer Science 2017-06-19 Luc Le Magoarou , Rémi Gribonval , Nicolas Tremblay

We present a novel and unifying framework for constructing spectral approximations to fractional integral operators. These spectral approximations are based on transplanted Chebyshev polynomials, which are obtained by composing Chebyshev…

Numerical Analysis · Mathematics 2026-04-30 Xiaolin Liu , Kuan Xu

The Fast Fourier Transform (FFT) over a finite field $\mathbb{F}_q$ computes evaluations of a given polynomial of degree less than $n$ at a specifically chosen set of $n$ distinct evaluation points in $\mathbb{F}_q$. If $q$ or $q-1$ is a…

Computational Complexity · Computer Science 2023-10-24 Songsong Li , Chaoping Xing

In this paper we propose a tool for high-dimensional approximation based on trigonometric polynomials where we allow only low-dimensional interactions of variables. In a general high-dimensional setting, it is already possible to deal with…

Numerical Analysis · Mathematics 2021-11-09 Felix Bartel , Daniel Potts , Michael Schmischke

Logarithms of determinants of large positive definite matrices appear ubiquitously in machine learning applications including Gaussian graphical and Gaussian process models, partition functions of discrete graphical models, minimum-volume…

Data Structures and Algorithms · Computer Science 2015-03-24 Insu Han , Dmitry Malioutov , Jinwoo Shin