# Signed measure

$\newcommand{\abs}{\left|#1\right|}$ An real-valued $\sigma$-additive function defined on a certain $\sigma$-algebra $\mathcal{B}$ of subsets of a set $X$. More generally one can consider vector-valued measures, i.e. $\sigma$-additive functions $\mu$ on $\mathcal{B}$ taking values on a Banach space $B$ (see Vector measure). The total variation measure of $\mu$ is defined on $B\in\mathcal{B}$ as: $\abs{\mu}(B) :=\sup\left\{ \sum \abs{\mu(B_i)}_B: \text{\{B_i\}\subset\mathcal{B} is a countable partition of B}\right\}$ where $\abs{\cdot}_B$ denotes the norm of $B$. In the real-valued case the above definition simplifies as $\abs{\mu}(B) = \sup_{A\in \mathcal{B}, A\subset B} \left(\abs{\mu (A)} + \abs{\mu (X\setminus B)}\right).$ $\abs{\mu}$ is a measure and $\mu$ is said to have finite total variation if $\abs{\mu} (X) <\infty$. If $V$ is finite-dimensional the [[Radon-Nikodym theorem]] implies the existence of a measurable $f\in L^1 (\abs{\mu}, V)$ such that $\mu (B) = \int_B f d\abs{\mu}\qquad \mbox{for all B\in\mathcal{B}.}$ In the case of real-valued measures this implies that each such $\mu$ can be written as the difference of two nonnegative measures $\mu^+$ and $\mu^-$ which are mutually singular (i.e. such that there are sets $B^+, B^-\in\mathcal{B}$ with $\mu^+ (X\setminus B^+)= \mu^- (X\setminus B^-) =\mu^+ (B^-)=\mu^- (B^+)=0$). This last statement is sometimes referred to as Hahn decomposition theorem. The Hahn decomposition theorem can also be proved defining directly the measures $\mu^+$ and $\mu^-$ in the following way: \begin{align*} \mu^+ (B) = \sup \{ \mu (A): A\in \mathcal{B}, A\subset B\}\\ \mu^- (B) = \sup \{ -\mu (A): A\in \mathcal{B}, A\subset B\} \end{align*} $\mu^+$ and $\mu^-$ are sometimes called, respectively, positive and negative variations of $\mu$. Observe that $|\mu| = \mu^++\mu^-$. By the [[Riesz representation theorem]] the space of signed measures with finite total variation on the Borel $\sigma$-algebra of a locally compact Hausdorff space is the dual of the space of continuous functions (cp. also with Convergence of measures).