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Let H = R with absolute value norm.
Example 4.1 Let H = R with absolute value norm.
Remark 2 We can associate to a given u ∈ Y an extended (i.e., admitting the infinite value) norm on Y denoted by ∥ ⋅ ∥ u and defined by ∥ v ∥ u : = inf { λ ∈ R + : | v | ≤ λ u }, v ∈ Y. From Theorem 1 we can easily deduce the following corollary.
The controller is based on the on-line solution of a robust performance test based on a Structured Singular Value norm.
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To do this, a functional analysis of value norms is required, and normative principles must be the result of the immediate context of valuation.
Hence, understanding local value norms and inculcating them into the communication packages can augment compulsory screen procedures.
Example F Let H = R with the absolute-value norm | ⋅ |.
Example C Let H = R with the absolute-value norm | ⋅ |.
Example A Let H = R with the absolute-value norm | ⋅ | and C = [ − 2, 0 ].
Example B Let H = R with the absolute-value norm | ⋅ | and C = [ 1 2, 2 ].
Example A Let X = R with the absolute-value norm | ⋅ | and C = [ 2, 10 ].
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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