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Multidimensional ESPRIT for Damped and Undamped Signals: Algorithm, Computations, and Perturbation Analysis
In this paper, we present and analyze the performance of multidimensional ESPRIT (<inline-formula> <tex-math notation="LaTeX">$N$</Tex-math></inline- formula>-D ESPRit) method for estimating parameters of large signals. Expand
Structured Low-Rank Approximation with Missing Data
The paper describes a solution method for matrix structured low-rank approximation, i.e., approximation of a given matrix by another matrix whose elements satisfy certain predefined relations. Expand
Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package
Implementation of multivariate and 2D extensions of singular spectrum analysis (SSA) by means of the R package Rssa. Expand
Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation
We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Expand
Software for weighted structured low-rank approximation
A software package is presented that computes locally optimal solutions to low-rank approximation problems with the following features: *mosaic Hankel structure constraint on the approximating matrix, *weighted 2-norm approximation criterion, *fixed elements in the data matrix, and *linear constraints on an approximation matrix's left kernel basis. Expand
Variable projection for affinely structured low-rank approximation in weighted 2-norms
The structured low-rank approximation problem for general affine structures, weighted 2-norms and fixed elements is considered. Expand
Factorization Approach to Structured Low-Rank Approximation with Applications
We consider the problem of approximating an affinely structured matrix, for example a Hankel matrix, by a low-rank matrix with the same structure. Expand
Hankel Low-Rank Matrix Completion: Performance of the Nuclear Norm Relaxation
  • K. Usevich, P. Comon
  • Mathematics, Computer Science
  • IEEE Journal of Selected Topics in Signal…
  • 26 February 2016
The completion of matrices with missing values under the rank constraint is a nonconvex optimization problem. Expand
Identifiability of an X-Rank Decomposition of Polynomial Maps
In this paper, we study a polynomial decomposition model that arises in problems of system identification, signal processing, and machine learning. Expand
2D-extension of Singular Spectrum Analysis: algorithm and elements of theory
Singular Spectrum Analysis is a nonparametric method, which allows one to solve problems like decomposition of a time series into a sum of interpretable components, extraction of periodic components,Expand