Mutual Information
Definitions
Let \(X\) and \(Y\) be discrete random variables defined on finite alphabets \(\mathcal{X}\) \(\mathcal{Y}\), respectively, and with joint probability mass function \(p_{X,Y}\). The mutual information of \(X\) and \(Y\) is the random variable \(I(X,Y)\) defined by
\[ I(X,Y) = \log\frac{p_{X,Y}(X,Y)}{p_X(X)p_Y(Y)}.\]