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B-Spline based Perfect Reconstruction of Non-band Limited Signals Through Noisy Sensors

Research Authors
G. Fahmy and M. Ihle
Research Department
Research Year
2013
Research Journal
IEEE International Symposium for Signal Processing and Information Technology, Athens, Dec, 2013
Research Publisher
NULL
Research Vol
NULL
Research Rank
3
Research_Pages
NULL
Research Website
NULL
Research Abstract

We consider the problem of sampling non band limited signals with a finite number of degrees of freedom such as non uniform splines or piecewise polynomials. These signals are typically called signals with finite rate of innovation (FRI). We propose a novel technique for perfectly reconstructing impulses of Diracs. These Diracs are our adopted non band limited signal and have been filtered specifically through a
B-spline sampling kernel, and then been uniformly sampled with a period T. This B-spline sampling kernel has an impulse response that is similar to most linear acquisition sensors/devices. The novelty of our proposed approach lies in the fact it is robust in noisy environments, unlike many recent
similar techniques, i.e. Dragotti el.[1] that may provide faster implementation but are very delicate with any type of noise. Our technique also does not have any restrictions on the number of perfectly reconstructed Diracs with respect to the sampling kernel order and achieves its reconstruction in
a B-spline 2-channel perfect reconstruction (PR) framework. A comparison of our proposed B-spline based perfect reconstruction system with the recent technique given in [1], in terms of speed, complexity, and kernel order complexity, is provided.