CONVOLUTION SAMPLING AND RECONSTRUCTION OF SIGNALS IN A REPRODUCING KERNEL SUBSPACE
Abbreviated Journal Title
Proc. Amer. Math. Soc.
Convolution sampling; reproducing kernel subspace; iterative algorithm; error estimate; SHIFT-INVARIANT SPACES; FINITE RATE; ITERATIVE RECONSTRUCTION; NOISY; SAMPLES; BANACH-SPACES; WIENERS LEMMA; INNOVATION; OPERATORS; HILBERT; SHANNON; Mathematics, Applied; Mathematics
We consider convolution sampling and reconstruction of signals in certain reproducing kernel subspaces of L-p, 1 <= p <= infinity. We show that signals in those subspaces could be stably reconstructed from their convolution samples taken on a relatively separated set with small gap. Exponential convergence and error estimates are established for the iterative approximation-projection reconstruction algorithm.
Proceedings of the American Mathematical Society
"CONVOLUTION SAMPLING AND RECONSTRUCTION OF SIGNALS IN A REPRODUCING KERNEL SUBSPACE" (2013). Faculty Bibliography 2010s. 4461.