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Prony's method under an almost sharp multivariate Ingham inequality

2017/05/31 by Stefan Kunis, Kunis, Stefan, H. Michael Möller +5
Computer Science · Engineering · Mathematics · #30E05 #42C15 #65F30 #65T40 #Advanced Numerical Analysis Techniques #Algebraic Geometry (math.AG) #Digital Filter Design and Implementation #FOS: Mathematics #Iterative Methods for Nonlinear Equations #Numerical Analysis (math.NA)

paper · pdf · doi:10.48550/arxiv.1705.11017

openalex publication_date 2017/05/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The parameter reconstruction problem in a sum of Dirac measures from its low frequency trigonometric moments is well understood in the univariate case and has a sharp transition of identifiability with respect to the ratio of the separation distance of the parameters and the order of moments. Towards a similar statement in the multivariate case, we present an Ingham inequality which improves the previously best known dimension-dependent constant from square-root growth to a logarithmic one. Secondly, we refine an argument that an Ingham inequality implies identifiability in multivariate Prony methods to the case of commonly used max-degree by a short linear algebra argument, closely related to a flat extension principle and the stagnation of a generalized Hilbert function.

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