Abstract
In this paper, we mainly study the average sampling and reconstruction of signals in a reproducing kernel subspace of the mixed Lebesgue space Lp,q(Rm+n). First, the sampling stability for two kinds of average sampling functionals is considered. Then, the corresponding iterative approximation projection algorithms with exponential convergence are established. Finally, the asymptotic pointwise error estimates are given for reconstructing a signal from its average samples corrupted by additive random noise.
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