Reconstruction of real and analytic band-pass signals from a finite number of samples

Abstract

In this paper, a theory for the reconstruction of real and analytic band-pass signals from a finite number of (sub) samples is developed, based on the concept of the analytic signal and band-pass subsampling. The main point is the dependence of the reconstruction error on the distribution of the zeros of the reconstruction kernel. Examples of such kernels are given, and the numerical results show the efficiency of the reconstruction methods presented, especially for the reconstruction from very few samples.