This paper presents a fast approximate rank-1 L1-norm Principal Component Analysis (L1-PCA) estimator implemented in the Fourier domain. Specifically, we first rephrase the problem of rank-1 L1-PCA estimation as a cyclic shift parameter estimation and then we present an algorithm for estimating the first L1-norm Principal Component (L1-PC) in the Fourier domain, practically using FFT. The proposed method is shown to be asymptotically efficient and our numerical studies corroborate its performance merits.

FFT calculation of the L1-norm principal component of a data matrix / Colonnese, S.; Markopoulos, P. P.; Scarano, G.; Pados, D. A.. - In: SIGNAL PROCESSING. - ISSN 0165-1684. - 189:(2021), pp. 1-9. [10.1016/j.sigpro.2021.108286]

FFT calculation of the L1-norm principal component of a data matrix

Colonnese S.;Scarano G.;
2021

Abstract

This paper presents a fast approximate rank-1 L1-norm Principal Component Analysis (L1-PCA) estimator implemented in the Fourier domain. Specifically, we first rephrase the problem of rank-1 L1-PCA estimation as a cyclic shift parameter estimation and then we present an algorithm for estimating the first L1-norm Principal Component (L1-PC) in the Fourier domain, practically using FFT. The proposed method is shown to be asymptotically efficient and our numerical studies corroborate its performance merits.
2021
cyclic shift; FFT; Fourier transform; L1-norm; L1-PCA
01 Pubblicazione su rivista::01a Articolo in rivista
FFT calculation of the L1-norm principal component of a data matrix / Colonnese, S.; Markopoulos, P. P.; Scarano, G.; Pados, D. A.. - In: SIGNAL PROCESSING. - ISSN 0165-1684. - 189:(2021), pp. 1-9. [10.1016/j.sigpro.2021.108286]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1567184
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