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The finite-total-variation signed measures form a real normed space
Statement
Fix a measurable space . With pointwise addition and scalar multiplication, is a real vector space. Moreover, defines a norm on it.
Facts & Assumptions
Given: A measurable space .
consists of the signed measures with . (The space of finite total variation signed measures)
Total variation is the supremum of unit-bounded simple integrals. (Total variation is the supremum of simple integrals over unit-bounded test functions)
A signed-measure null set is exactly a set of zero total variation. (A set is null for a signed measure exactly when its total variation is zero there)
A normed space is a real vector space together with a norm satisfying separation, absolute homogeneity, and the triangle inequality. (Vector space over a field, A norm on a real vector space, the induced metric, and the dictionary with the metric axioms)
Proof
If and , then the [L1, L2, L4] pointwise set functions and are again signed measures because their values are finite on every measurable set and countable additivity is preserved termwise. Also [L2] gives so and remain in . Thus is closed under the pointwise operations, and the vector-space axioms are inherited from the real-valued function space on .
The formula is nonnegative by definition. If , [L1, L3, L4] then [L3] makes null for , so every measurable set has -value and therefore is the zero measure. Conversely the zero measure has variation . Thus the separation axiom of [L4] holds.
Step 1.1 already proved absolute homogeneity and the triangle inequality: [L2, L4, step 1.1] Hence [L4] shows that is a norm.
Steps 1.1 through 2.1 prove that is a real [step 1.1, step 1.2, step 2.1] ∎ normed space.
Depends on
- The space of finite total variation signed measures
- Total variation is the supremum of simple integrals over unit-bounded test functions
- A set is null for a signed measure exactly when its total variation is zero there
- Vector space over a field
- A norm on a real vector space, the induced metric, and the dictionary with the metric axioms
Used by
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Sources
- Sheldon Axler, Measure, Integration & Real Analysis, Theorem 9.13 (standard reference, not scraped)
- Richard F. Bass, Real Analysis for Graduate Students, Exercise 12.5 (standard reference, not scraped)