Digital Signal Processing Reference
In-Depth Information
Figure 9.4
Decomposition of a periodic sampling point process with random skips into
various components in the case of additive random sampling
decomposition all of the signal sample values are subdivided nonequally between
the
n
components of the particular
n
th decomposition.
Periodic Sampling with Jitter
Figure 9.5 illustrates the decomposition of periodic sampling points with jitter.
In this case the features of the obtained decompositions differ from the charac-
teristic features of the decompositions obtained when the primary sampling point
process belongs to the class of additive pseudo-random sampling. Specifically,
the periodic sampling points with jitter are decomposed into only three out of
eight components. The remaining five other components are empty and do not
contain any sampling points. Therefore the conclusion is found that a spectrogram
obtained by performing a DFT for a pseudo-randomly sampled signal contains,
in addition to estimates of the signal components, multiple aliases due to the
primary and the secondary aliasing effects.
The decomposition of the randomized sampling point sequences is an approach
that is convenient for studies of various processes related to processing of signals
sampled in this way. It can also be used both for analysis of various processes
and synthesis of algorithms. For instance, the usefulness of this decomposition
