High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?

Konstantin Usevich 1 Souleymen Sahnoun 1 Pierre Comon 1
1 GIPSA-CICS - CICS
GIPSA-DIS - Département Images et Signal
Abstract : In subspace-based methods for mulditimensional harmonic retrieval, the modes can be estimated either from eigenvalues or eigen-vectors. The purpose of this study is to find out which way is the best. We compare the state-of-the art methods N-D ESPRIT and IMDF, propose a modification of IMDF based on least-squares criterion, and derive expressions of the first-order perturbations for these methods. The theoretical expressions are confirmed by the computer experiments.
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Submitted on : Thursday, August 24, 2017 - 11:54:53 AM
Last modification on : Friday, July 27, 2018 - 11:24:29 AM

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Konstantin Usevich, Souleymen Sahnoun, Pierre Comon. High-Resolution Subspace-Based Methods: Eigenvalue- or Eigenvector-Based Estimation?. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA-ICA 2017), Feb 2017, Grenoble, France. pp.47-56, ⟨10.1007/978-3-319-53547-0_5⟩. ⟨hal-01576895⟩

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