FDTD near field data reduction using principal component analysis

Ramos, Glaucio Lopes; Rodrigues, Gustavo Fernandes; Rego, C.G.

doi:10.1109/imoc.2015.7369117

Cited by 1 publication

(1 citation statement)

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“…The PCA technique has been frequently applied in data reduction [7][8][9][10], and it will be compared in this work with a statistical analysis used to perform the same task. The PCA compression reduction on near-field data compression was tested before for a half-wavelength dipole and an array of dipoles [11], and in this work, it will be also evaluated to a scattered field by a dielectric sphere.…”

Section: Introductionmentioning

confidence: 99%

Comparison between statistical and principal component analysis in reduction of near‐field FDTD data

Ramos¹,

Rodrigues

Camilo

et al. 2019

IET Microwaves, Antennas & Propagation

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We present a comparison of statistical and principal component analyses (PCA) for reducing the amount of near‐field data required as an input to a time‐domain spherical‐multipole near‐to‐far‐field transformation. Such transformations are necessary for finite‐difference time‐domain (FDTD) simulations that typically only model the near‐field. The authors demonstrate their approach for the case of far‐fields scattered by a dielectric sphere. For a threshold value of 106, the PCA technique reduced the data required by 32%, using 12 components. A similar compression was achieved with statistical analysis, when the threshold is set at 10−7σ. Their work shows that the proposed statistical compression is preferable because it has simpler implementation and low‐cost processing, when implemented together with the NFF transformation code.

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