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We show that the condition number of any cyclically contiguous $p\times q$ submatrix of the $N\times N$ discrete Fourier transform (DFT) matrix is at least $$ \exp \left( \frac{\pi}{2} \left[\min(p,q)- \frac{pq}{N}\right] \right)~, $$ up to…

Numerical Analysis · Mathematics 2020-08-17 Alex H. Barnett

The discrete Fourier transform matrix is one of the most important matrices in linear algebra, and submatrices of it arise in a variety of applications. Though the discrete Fourier transform matrix is unitary, its submatrices can be…

Numerical Analysis · Mathematics 2026-04-30 Rikhav Shah , John Urschel

Vandermonde matrices are exponentially ill-conditioned, rendering the familiar "polyval(polyfit)" algorithm for polynomial interpolation and least-squares fitting ineffective at higher degrees. We show that Arnoldi orthogonalization fixes…

Numerical Analysis · Mathematics 2019-11-25 Pablo D. Brubeck , Yuji Nakatsukasa , Lloyd N. Trefethen

In this paper, we investigate the Kirkwood-Dirac nonclassicality and uncertainty diagram based on discrete Fourier transform (DFT) in a $d$ dimensional system. The uncertainty diagram of complete incompatibility bases $\mathcal {A},\mathcal…

Quantum Physics · Physics 2023-08-03 Ying-Hui Yang , Bing-Bing Zhang , Xiao-Li Wang , Shi-Jiao Geng , Pei-Ying Chen

Different types of convolution operations involving large Vandermonde matrices are considered. The convolutions parallel those of large Gaussian matrices and additive and multiplicative free convolution. First additive and multiplicative…

Information Theory · Computer Science 2016-11-15 Ø. Ryan , M. Debbah

Bernstein polynomials, long a staple of approximation theory and computational geometry, have also increasingly become of interest in finite element methods. Many fundamental problems in interpolation and approximation give rise to…

Numerical Analysis · Mathematics 2020-05-08 Larry Allen , Robert C. Kirby

Contiguous submatrices of the Fourier matrix are known to be ill-conditioned. In a recent paper in SIAM Review A. Barnett has provided new bounds on the rate of ill-conditioning of the discrete Fourier submatrices. In this paper we focus on…

Numerical Analysis · Mathematics 2022-08-29 Simon Dirckx , Daan Huybrechs , Robbe Ongenae

Random matrices tend to be well conditioned, and we employ this well known property to advance matrix computations. We prove that our algorithms employing Gaussian random matrices are efficient, but in our tests the algorithms have…

Numerical Analysis · Mathematics 2012-10-30 Victor Y. Pan , Guoliang Qian , Ai-Long Zheng

The author was encouraged to write this review by numerous enquiries from researchers all over the world, who needed a ready-to-use algorithm for the inversion of confluent Vandermonde matrices which works in quadratic time for any values…

History and Overview · Mathematics 2026-04-10 Jerzy S Respondek

Motivated by a host of recent applications requiring some amount of redundancy, frames are becoming a standard tool in the signal processing toolbox. In this paper, we study a specific class of frames, known as discrete Fourier transform…

Information Theory · Computer Science 2015-06-05 Mojtaba Vaezi , Fabrice Labeau

Motivated by a host of recent applications requiring some amount of redundancy, frames are becoming a standard tool in the signal processing toolbox. In this paper, we study a specific class of frames, known as discrete Fourier transform…

Information Theory · Computer Science 2012-05-23 Mojtaba Vaezi , Fabrice Labeau

In 1989 we proposed to employ Vandermonde and Hankel multipliers to transform into each other the matrix structures of Toeplitz, Hankel, Vandermonde and Cauchy types as a means of extending any successful algorithm for the inversion of…

Numerical Analysis · Mathematics 2013-03-05 Victor Y. Pan

Matrices with the structures of Toeplitz, Hankel, Vandermonde and Cauchy types are omnipresent in modern computation. The four classes have distinct features, but in 1990 we showed that Vandermonde and Hankel multipliers transform all these…

Numerical Analysis · Mathematics 2013-11-18 Victor Y. Pan

This paper is concerned with computations of a few smaller eigenvalues (in absolute value) of a large extremely ill-conditioned matrix. It is shown that smaller eigenvalues can be accurately computed for a diagonally dominant matrix or a…

Numerical Analysis · Mathematics 2017-05-16 Qiang Ye

Inverse Vandermonde matrix calculation is a long-standing problem to solve nonsingular linear system $Vc=b$ where the rows of a square matrix $V$ are constructed by progression of the power polynomials. It has many applications in…

Numerical Analysis · Mathematics 2019-09-19 Mahdi S. Hosseini , Alfred Chen , Konstantinos N. Plataniotis

The classical result of Vandermonde decomposition of positive semidefinite Toeplitz matrices, which dates back to the early twentieth century, forms the basis of modern subspace and recent atomic norm methods for frequency estimation. In…

Information Theory · Computer Science 2017-07-24 Zai Yang , Lihua Xie

We prove explicit lower bounds for the smallest singular value and upper bounds for the condition number of rectangular, multivariate Vandermonde matrices with scattered nodes on the complex unit circle. Analogously to the Shannon-Nyquist…

Numerical Analysis · Mathematics 2021-03-16 Stefan Kunis , Dominik Nagel , Anna Strotmann

We present extensive first principles density functional theory (DFT) calculations dedicated to analyze the magnetic and electronic properties of small V$_{n}$ clusters (n=1,2,3,4,5,6) embedded in a Cu fcc matrix. We consider different…

Strongly Correlated Electrons · Physics 2015-05-18 R. E. Felix-Medina , M. A. Leyva-Lucero , R. A. Guirado-Lopez , S. Meza-Aguilar

A generalization of the Vandermonde matrices which arise when the power basis is replaced by the Said-Ball basis is considered. When the nodes are inside the interval (0,1), then those matrices are strictly totally positive. An algorithm…

Numerical Analysis · Mathematics 2008-12-17 Ana Marco , Jose-Javier Martinez

Semidefinite programs (SDPs) -- some of the most useful and versatile optimization problems of the last few decades -- are often pathological: the optimal values of the primal and dual problems may differ and may not be attained. Such SDPs…

Optimization and Control · Mathematics 2019-10-23 Gabor Pataki
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