Multivariate exponential analysis from the minimal number of samples

Citation

Cuyt A & Lee W (2018) Multivariate exponential analysis from the minimal number of samples. Advances in Computational Mathematics, 44 (4), pp. 987-1002. https://doi.org/10.1007/s10444-017-9570-8

Abstract
The problem of multivariate exponential analysis or sparse interpolation has received a lot of attention, especially with respect to the number of samples required to solve it unambiguously. In this paper we show how to bring the number of samples down to the absolute minimum of (d + 1)n where d is the dimension of the problem and n is the number of exponential terms. To this end we present a fundamentally different approach for the multivariate problem statement. We combine a one-dimensional exponential analysis method such as ESPRIT, MUSIC, the matrix pencil or any Prony-like method, with some linear systems of equations because the multivariate exponents are inner products and thus linear expressions in the parameters.

Keywords
Exponential sum; Multivariate; Prony’s method

Journal
Advances in Computational Mathematics: Volume 44, Issue 4

People

Dr Wen-shin Lee

Lecturer, Computing Science and Mathematics - Division