  Random sampling is a technique for signal acquisition which is gaining
popularity in practical signal processing systems. Nowadays, event-driven
analog-to-digital converters make random sampling feasible in practical
applications. A process of random sampling is defined by a sampling pattern,
which indicates signal sampling points in time. Practical random sampling
patterns are constrained by ADC characteristics and application requirements.
In this paper authors introduce statistical methods which evaluate random
sampling pattern generators with emphasis on practical applications.
Furthermore, the authors propose a new random pattern generator which copes
with strict practical limitations imposed on patterns, with possibly minimal
loss in randomness of sampling. The proposed generator is compared with
existing sampling pattern generators using the introduced statistical methods.
It is shown that the proposed algorithm generates random sampling patterns
dedicated for event-driven-ADCs better than existed sampling pattern
generators. Finally, implementation issues of random sampling patterns are
discussed.
