  When sampling multiple signals, the correlation between the signals can be
exploited to reduce the overall number of samples. In this paper, we study the
sampling theory of multiple correlated signals, using correlation to sample
them at the lowest sampling rate. Based on the correlation between signal
sources, we model multiple continuous-time signals as continuous time-vertex
graph signals. The graph signals are projected onto orthogonal bases to remove
spatial correlation and reduce dimensions by graph Fourier transform. When the
bandwidths of the original signals and the reduced dimension signals are given,
we prove the minimum sampling rate required for recovery of the original
signals, and propose a feasible sampling scheme.
