Postfiltering versus prefiltering for signal recovery from noisy samples
We consider the extension of the Whittaker-Shannon (WS) reconstruction formula to the case of signals sampled in the presence of noise and which are not necessarily band limited. Observing that in this situation the classical sampling expansion yields inconsistent reconstruction, we introduce a class of signal recovery methods with a smooth correction of the interpolation series. Two alternative data smoothing methods are examined based either on a global postfiltering or a local data presmoothing. We assess the accuracy of the methods by the global L-2 error. Both band-limited and non-band-limited signals are considered. A general class of correlated noise processes is taken into account. The weak and strong rates of convergence of the algorithms are established and their relative efficiency is discussed. The influence of noise memory and its moment structure on the accuracy is thoroughly examined.
band-limited signals, non-band-limited signals, postfiltering, prefiltering, rate of convergence, signal recovery, strong convergence, Whittaker-Shannon (WS) sampling theorem, BAND-LIMITED SIGNALS, FOURIER-ANALYSIS, APPROXIMATIONS, THEOREM, ERROR
0018-9448; IEEE TRANS INFORM THEORY, DEC 2003, vol. 49, no. 12, p.3195 to 3212.