An improved convergence rate of A-P reconstruction algorithm and application in signal processing

This paper presents a reconstruction formula in general shift-invariant signal spaces that improve the rate of A-P iterative algorithm. We use the algorithm to show reconstruction of signals from weighted samples and also show that there is better convergence than the old one. We study the algorithm with emphasis on its implementation in field of signal processing, which the signal spaces is sufficiently large to accommodate a large number of possible models. Numerical examples results are furnished to illustrate our results.