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Exact(2)
If f: X1→ X2 is a additive (quadratic) function, then f (rx) = rf (x) (f (rx) = r2f (x)), for all x ∈ X1 and all r ∈ ℚ. .
Assuming that the eigenvalues of the signal and noise in (11) are, respectively, λ 1,λ 2,⋯λ 2K and λ 2K+1,λ 2K+2,⋯λ 4M with ({lambda _{1}} geqslant {lambda _{2}} geqslant cdots geqslant {lambda _{4M}}), it is well known that, if the noise in a vector array is a additive white noise, the eigenvalues of the noise subspace of an ideal data covariance matrix are equal, i.e. λ 2K+1=λ 2K+1=λ=λ 4M.
Similar(58)
and an odd mapping f : X → Ysatisfies Equation 1 if and only if the odd mapping f :X → Y is a additive-cubic mapping, thatis, f ( 2 x + y ) + f ( 2 x − y ) = 4 { f ( x + y ) + f ( x − y ) } − 6 f ( x ).
It is an additive category.
The xsnlapec model is an additive model component.
The xsbvrnei model is an additive model component.
The xscutoffpl model is an additive model component.
The xstapec model is an additive model component.
The xsvvgnei model is an additive model component.
The xscomptt model is an additive model component.
The xsvapec model is an additive model component.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com