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Diffstat (limited to 'site/content/gsoc/otsu2018_3.typ')
| -rw-r--r-- | site/content/gsoc/otsu2018_3.typ | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/content/gsoc/otsu2018_3.typ b/site/content/gsoc/otsu2018_3.typ index aa1666e..c37b8d8 100644 --- a/site/content/gsoc/otsu2018_3.typ +++ b/site/content/gsoc/otsu2018_3.typ @@ -5,7 +5,7 @@ date: datetime(year: 2020, month: 7, day: 26), ) -In the #link-self("gsoc/otsu2018_2")[previous post] I explained how PCA can be used to create a convenient basis for representing real-world reflectivities. The procedure uses a set of measured spectra to compute an orthonormal basis, sorted by variance or "statistical significance." All but the three most significant vectors are then truncated. I called the difference between the actual spectrum and the reconstructed error term $bold(epsilon)$. +In the #link-self("gsoc/otsu2018_2")[previous post] I explained how PCA can be used to create a convenient basis for representing real-world reflectivities. The procedure uses a set of measured spectra to compute an orthonormal basis, sorted by variance or "statistical significance." All but the three most significant vectors are then truncated. I called the difference between the actual spectrum and the reconstructed spectrum the error term $bold(epsilon)$. Naturally the smaller the error, the better. Because $bold(epsilon)$ is a vector, the authors chose the Euclidean norm (2-norm or L2) to represent the (scalar) error: $ |