I am reviewing a paper titled " Bayesian Sampling Approach to Decision Fusion" by Biao Chen and Pramod K Varshney. This paper uses an indicator function that I am not being able understand. The indicator function is used as follows
$I_{\mathbf{U}=g(\mathbf{X})}=1\hspace{5mm}if \hspace{5mm}\mathbf{U}=g(\mathbf{X}) \\ =0 \hspace{5mm} otherwise\\$
$\\where,\hspace{5mm} U_i=g(X_i)=0, \hspace{5mm} if \hspace{5mm} X_i \leq \tau \\ =1,\hspace{5mm} if \hspace{5mm} X_i \geq \tau$
where $X_i$ is observation at individual sensors, $U_i$ is the decision made at individual sensors and $\mathbf{X}$ is the vector of observation. How do you interpret indicator function in this case?The paper discussing about formulation is mentioned here