  Data saving capability of "Compressed sensing (sampling)" in signal
discretization is disputed and found to be far below the theoretical upper
bound defined by the signal sparsity. On a simple and intuitive example, it is
demonstrated that, in a realistic scenario for signals that are believed to be
sparse, one can achieve a substantially larger saving than compressing sensing
can. It is also shown that frequent assertions in the literature that
"Compressed sensing" can beat the Nyquist sampling approach are misleading
substitution of terms and are rooted in misinterpretation of the sampling
theory.
