Almost sure identifiability of multidimensional harmonic retrieval

Tao Jiang, Nicholas D. Sidiropoulos, Jos M.F. Ten Berge

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Two-dimensional (2-D) and more generally multi-dimensional harmonic retrieval is of interest in a variety of applications. The associated identifiability problem is key in understanding the fundamental limitations of parametric high-resolution methods. In the 2-D case, existing identifiability results indicate that, assuming sampling at Nyquist or above, the number of resolvable exponentials is proportional to I + J, where I is the number of (equispaced) samples along one dimension, and J likewise for the other dimension. We prove in this paper that the number of resolvable exponentials is roughly I J/4, almost surely. This is not far from the equations-versus-unknowns bound of I J/3. We then generalize the result to the N-D case for any N > 2, showing that, under quite general conditions, the number of resolvable exponentials is proportional to total sample size, hence grows exponentially with the number of dimensions.

Original languageEnglish (US)
Pages (from-to)3093-3096
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
DOIs
StatePublished - 2001

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