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.File | Dimensione | Formato | |
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