High-resolution subspace-based methods: Eigenvalue- or eigenvector-based estimation?

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Abstract

In subspace-based methods for mulditimensional harmonic retrieval, the modes can be estimated either from eigenvalues or eigenvectors. 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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Usevich, K., Sahnoun, S., & Comon, P. (2017). High-resolution subspace-based methods: Eigenvalue- or eigenvector-based estimation? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10169 LNCS, pp. 47–56). Springer Verlag. https://doi.org/10.1007/978-3-319-53547-0_5

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