Compensating Interpolation Distortion by Using New Optimized Modular Method
This addresses signal processing issues for applications requiring accurate signal recovery from interpolated samples, but it appears incremental as it builds on prior modular methods.
The paper tackles the problem of distortion in interpolation-based signal recovery by proposing an optimized modular method that adds simply calculated coefficients to improve performance. The result is a drastic improvement in signal-to-noise ratios with fewer modules and superior robustness against additive noise compared to classical methods.
A modular method was suggested before to recover a band limited signal from the sample and hold and linearly interpolated (or, in general, an nth-order-hold) version of the regular samples. In this paper a novel approach for compensating the distortion of any interpolation based on modular method has been proposed. In this method the performance of the modular method is optimized by adding only some simply calculated coefficients. This approach causes drastic improvement in terms of signal-to-noise ratios with fewer modules compared to the classical modular method. Simulation results clearly confirm the improvement of the proposed method and also its superior robustness against additive noise.