Title :
Multi-Stage Robust Chinese Remainder Theorem
Author :
Li Xiao ; Xiang-Gen Xia ; Wenjie Wang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA
Abstract :
It is well-known that the traditional Chinese remainder theorem (CRT) is not robust in the sense that a small error in a remainder may cause a large reconstruction error. A robust CRT was recently proposed for a special case when the greatest common divisor (gcd) of all the moduli is more than 1 and the remaining integers factorized by the gcd are co-prime. It basically says that the reconstruction error is upper bounded by the remainder error level τ if τ is smaller than a quarter of the gcd of all the moduli. In this paper, we consider the robust reconstruction problem for a general set of moduli. We first present a necessary and sufficient condition on the remainder errors with a general set of moduli and also a corresponding robust reconstruction method. This can be thought of as a single-stage robust CRT. We then propose a two-stage robust CRT by grouping the moduli into several groups as follows. First, the single-stage robust CRT is applied to each group. Then, with these robust reconstructions from all the groups, the single-stage robust CRT is applied again across the groups. This is easily generalized to multi-stage robust CRT. With this two-stage robust CRT, the robust reconstruction holds even when the remainder error level τ is above the quarter of the gcd of all the moduli, and an algorithm on how to group a set of moduli for a better reconstruction robustness is proposed in some special cases.
Keywords :
signal reconstruction; GCD; greatest common divisor; large reconstruction error; moduli; multistage robust chinese remainder theorem; necessary condition; remainder error level; robust reconstruction method; single-stage robust CRT; sufficient condition; upper bound; Dynamic range; Educational institutions; Electronic mail; Reconstruction algorithms; Robustness; Signal processing algorithms; Silicon; Chinese remainder theorem; frequency estimation from undersamplings; greatest common divisor; moduli; robustness;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2014.2339798