Principal Component Analysis of Results Obtained from Finite-Difference Time-Domain Algorithms



Downloads per month over past year

López Alonso, José Manuel and Rico-García, José María and Alda, Javier (2006) Principal Component Analysis of Results Obtained from Finite-Difference Time-Domain Algorithms. Egyptian Journal of Solids, 29 (1). pp. 19-34. ISSN 1012-5566

[thumbnail of Principal component-EgyptJSolid_2006.pdf]

Official URL:


Finite-Differences Time-Domain (FDTD) algorithms are well established tools of computational electromagnetism. Because of their practical implementation as computer codes, they are affected by many numerical artefact and noise. In order to obtain better results we propose using Principal Component Analysis (PCA) based on multivariate statistical techniques. The PCA has been successfully used for the analysis of noise and spatial temporal structure in a sequence of images. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic variables, and the quantitative estimation of their respective contributions. Besides, The GDTD results can be filtered to clean the effect of the noise. In this contribution we will show how the method can be applied to several FDTD simulations: the propagation of a pulse in vacuum, the analysis of two-dimensional photonic crystals. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.

Item Type:Article
Additional Information:

Accesible a texto completo en la web del editor.

Uncontrolled Keywords:Finite-Differences Time-Domain ; (FDTD) ; computational electromagnetism ; Principal Component Analysis (PCA) ; photonic crystal
Subjects:Sciences > Physics > Electromagnetism
Sciences > Physics > Optics
Medical sciences > Optics > Physical optics
ID Code:38616
Deposited On:07 Sep 2016 12:44
Last Modified:07 Sep 2016 12:44

Origin of downloads

Repository Staff Only: item control page