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This paper is concerned with the solution of large-scale linear discrete ill-posed problems with error-contaminated data. Tikhonov regularization is a popular approach to determine meaningful approximate solutions of such problems. The…

Numerical Analysis · Mathematics 2016-02-11 Guangxin Huang , Silvia Noschese , Lothar Reichel

Given a matrix $A$, a matrix nearness problem seeks an $X$ that most closely approximates $A$ in the sense of minimizing $\lVert A - X\rVert$ under a variety of constraints on $X$. A generalized matrix nearness problem seeks the same but…

Numerical Analysis · Mathematics 2026-05-29 Rongbiao Thomas Wang , Chi-Kwong Li , Lek-Heng Lim

Given a matrix-valued function $\mathcal{F}(\lambda)=\sum_{i=1}^d f_i(\lambda) A_i$, with complex matrices $A_i$ and $f_i(\lambda)$ entire functions for $i=1,\ldots,d$, we discuss a method for the numerical approximation of the distance to…

Numerical Analysis · Mathematics 2025-04-11 Miryam Gnazzo , Nicola Guglielmi

When approximating elliptic problems by using specialized approximation techniques, we obtain large structured matrices whose analysis provides information on the stability of the method. Here we provide spectral and norm estimates for…

Numerical Analysis · Mathematics 2023-03-23 Armando Coco , Sven-Erik Ekström , Giovanni Russo , Stefano Serra-Capizzano , Santina Chiara Stissi

This paper studies two structured approximation problems: (1) Recovering a corrupted low-rank Toeplitz matrix and (2) recovering the range of a Fourier matrix from a single observation. Both problems are computationally challenging because…

Information Theory · Computer Science 2025-11-24 Albert Fannjiang , Weilin Li

We address the problem of finding the nearest graph Laplacian to a given matrix, with the distance measured using the Frobenius norm. Specifically, for the directed graph Laplacian, we propose two novel algorithms by reformulating the…

Optimization and Control · Mathematics 2024-04-05 Kazuhiro Sato , Masato Suzuki

Examining the extent to which measurements of rotation matrices are close to each other is challenging due measurement noise. To overcome this, data is typically smoothed and Riemannian and Euclidean metrics are applied. However, if…

Numerical Analysis · Mathematics 2025-02-19 P. D. Ledger , W. R. B. Lionheart , J. Elgy

In this work, we consider symmetric random Toeplitz matrices $T_n$ generated by i.i.d. zero mean random variables ${X_k}$ satisfying the moment conditions: $E|X_k|^2=1$ and $\E|X_1|^n \le n^{\sqrt{n}}$ for all $n\ge 3$. We prove that the…

Probability · Mathematics 2013-01-10 Malika Kharouf

Consider random symmetric Toeplitz matrices $T_{n}=(a_{i-j})_{i,j=1}^{n}$ with matrix entries $a_{j}, j=0,1,2,...,$ being independent real random variables such that \be \mathbb{E}[a_{j}]=0, \ \ \mathbb{E}[|a_{j}|^{2}]=1 \ \ \textrm{for}\,\…

Probability · Mathematics 2010-11-09 Dang-Zheng Liu , Xin Sun , Zheng-Dong Wang

Almost-commuting matrices with respect to the normalized Hilbert-Schmidt norm are considered. Normal almost commuting matrices are proved to be near commuting.

Algebraic Geometry · Mathematics 2010-02-17 Lev Glebsky

We consider the symmetric Toeplitz matrix completion problem, whose matrix under consideration possesses specific row and column structures. This problem, which has wide application in diverse areas, is well-known to be computationally…

Optimization and Control · Mathematics 2024-03-15 Xihong Yan , Jiahao Guo , Yi Xu

In this paper, we study the condition number of a random Toeplitz matrix. Since a Toeplitz matrix is a diagonal constant matrix, its rows or columns cannot be stochastically independent. This situation does not permit us to use the classic…

Probability · Mathematics 2020-09-30 Paulo Manrique--Mirón

The problem of finding the distance from a given $n \times n$ matrix polynomial of degree $k$ to the set of matrix polynomials having the elementary divisor $(\lambda-\lambda_0)^j, \, j \geqslant r,$ for a fixed scalar $\lambda_0$ and $2…

Numerical Analysis · Mathematics 2019-11-05 Biswajit Das , Shreemayee Bora

We provide in this work an algorithm for approximating a very broad class of symmetric Toeplitz matrices to machine precision in $\mathcal{O}(n \log n)$ time with applications to fitting time series models. In particular, for a symmetric…

Numerical Analysis · Mathematics 2024-11-22 Christopher J. Geoga

We consider the problem of computing the closest stable/unstable non-negative matrix to a given real matrix. This problem is important in the study of linear dynamical systems, numerical methods, etc. The distance between matrices is…

Dynamical Systems · Mathematics 2018-02-12 Nicola Guglielmi , Vladimir Yu. Protasov

We consider partial symmetric Toeplitz matrices where a positive definite completion exists. We characterize those patterns where the maximum determinant completion is itself Toeplitz. We then extend these results with positive definite…

Optimization and Control · Mathematics 2018-02-05 Stefan Sremac , Hugo J. Woerdeman , Henry Wolkowicz

We show that the limiting eigenvalue distribution of random symmetric Toeplitz matrices is absolutely continuous with density bounded by 8, partially answering a question of Bryc, Dembo and Jiang (2006). The main tool used in the proof is a…

Probability · Mathematics 2022-04-27 Arnab Sen , Bálint Virág

The trace approximation problem for Toeplitz matrices and its applications to stationary processes dates back to the classic book by Grenander and Szeg\"o, "Toeplitz forms and their applications". It has then been extensively studied in the…

Probability · Mathematics 2013-04-25 Mamikon S. Ginovyan , Artur A. Sahakyan , Murad S. Taqqu

In this paper, we consider the problem of seriation of a permuted structured matrix based on noisy observations. The entries of the matrix relate to an expected quantification of interaction between two objects: the higher the value, the…

Statistics Theory · Mathematics 2025-07-21 Clément Berenfeld , Alexandra Carpentier , Nicolas Verzelen

Our main interest is the low-rank approximation of a matrix in R^m.n under a weighted Frobenius norm. This norm associates a weight to each of the (m x n) matrix entries. We conjecture that the number of approximations is at most min(m, n).…

Applications · Statistics 2013-02-05 William Rey