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The Lebesgue decomposition of a sigma-finite signed measure is unique
Statement
Let be a positive measure and let be a signed measure satisfying the common finite-exhaustion hypothesis of Every sigma-finite signed measure admits a Lebesgue decomposition relative to a sigma-finite positive measure. If with and , then
Facts & Assumptions
Given: Two Lebesgue decompositions of the same signed measure relative to a positive measure .
A measure concentrated on a -null set is singular with respect to . (A positive, signed, or complex measure concentrated on a measurable set)
A signed or complex measure that is both absolutely continuous and singular with respect to is zero. (A signed or complex measure that is both absolutely continuous and singular with respect to the same positive measure is zero)
Proof
Subtract the two decompositions to obtain The left-hand side is absolutely continuous with respect to , because differences of absolutely continuous measures are again absolutely continuous.
Choose -null sets and on which and are concentrated. Then is concentrated on , which is still -null, so [L1] makes the right-hand side singular with respect to .
The common difference in steps 1.1 and 1.2 is therefore both absolutely continuous and singular with respect to , so [L2] forces . Substituting back into the decomposition identity gives as well.
Depends on
- A positive, signed, or complex measure concentrated on a measurable set
- A signed or complex measure that is both absolutely continuous and singular with respect to the same positive measure is zero
- Every sigma-finite signed measure admits a Lebesgue decomposition relative to a sigma-finite positive measure
Used by
- The absolutely continuous part and the singular part in the Lebesgue decomposition Definition
- The Lebesgue decomposition of one half Lebesgue plus one half Cantor measure Example
- Every finite Borel measure on R has a unique absolutely continuous, discrete, and singular-continuous decomposition Theorem
Dependency tree · two levels
16 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Richard F. Bass, Real Analysis for Graduate Students, Theorem 13.5 (standard reference, not scraped)
- Sheldon Axler, Measure, Integration & Real Analysis, 9.35 (standard reference, not scraped)