TheoremBase

Norms and Real Normed Spaces

A norm on a real vector space is a nonnegative, definite, absolutely homogeneous real-valued function satisfying the triangle inequality; a real normed space is a real vector space with a norm.

Statement

In the setting of The Real Numbers, with the Natural Numbers, Integers and Rationals Identified with Subsets of the Reals, and Completeness, let VV, with its addition and scalar multiplication, be a real vector space, with zero vector 0V0_{V}, and let ∥⋅∥:V→R\lVert\cdot\rVert:V\to\mathbb{R}, v↦∥v∥v\mapsto\lVert v\rVert, be a function. The conditions below are required for all u,v∈Vu,v\in V and all λ∈R\lambda\in\mathbb{R}.

Nonnegativity. ∥v∥≥0\lVert v\rVert\ge0.

Definiteness. If ∥v∥=0\lVert v\rVert=0, then v=0Vv=0_{V}.

Absolute homogeneity. ∥λv∥=∣λ∣ ∥v∥\lVert\lambda v\rVert=|\lambda|\,\lVert v\rVert.

Triangle inequality. ∥u+v∥≤∥u∥+∥v∥\lVert u+v\rVert\le\lVert u\rVert+\lVert v\rVert.

Norm. ∥⋅∥\lVert\cdot\rVert is a norm on VV if it satisfies (i), (ii), (iii) and (iv).

Real normed space. A real normed space (V,∥⋅∥)(V,\lVert\cdot\rVert) is a real vector space VV together with a norm ∥⋅∥\lVert\cdot\rVert on VV.

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