SPARSITY ASSISTED SIGNAL SMOOTHING IN TIME-SERIES SEISMIC DATA
Abhishek Kesharwani, DEVIKA CHIB, Shubham Kumar Singh, Malaya Kumar Hota · INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY · 2020
Sparsity-assisted signal smoothing (SASS) is dependent on a banded matrix formulation of the recursive filtering of finite length input signals.This paper presents a formulation of higher-order zero-phase lowpass, high-pass, and band-pass infinite impulse response filters as matrices, using the spectral transformation of the statespace representation of digital filters, that avoids the unwanted transient artifacts at signal end-points in the original formulation and denoises marine seismic signals.The simulations have been created by running the code in MATLAB, using synthesized data, thus the results can be compared with the other methods easily.The problems posed while noise removal by conventional methods are also discussed.We have tried our best in presenting this new technology and the output obtained for the same clearly indicates the effectiveness and robustness of a SASS denoising algorithm and has a wide scope of application in the future, which can be a very important asset to the research process.