M. Beena Mol, J. Mohanalin, S. Prabavathy, Domènec Puig, “A Novel Wavelet Seismic Dengising Method Using Type II Fuzzy”, Article, August 2016 DOI: 10.1016pj.asoc.2016.06.024
Abstract
Wavelet based denoising of the observed non stationary time series earthquake loading has become an important process tn seismic analysis. The process of denoising ensures a noise free seismic data, which is essential to extract features accurately (m-x acceleration, max velocity, max displacement etc.). However, the efficiency of wavelet denoising is decided by the identification of a crucial factor called thresholt. But, identification of optimal ihreshold is not a straight forward proces” as the signal involved is non-stationary. i.e The information whtch separates dhe wavelet coefficients that correspond to the region of interest from the noisy wavelet coefficients is vague and fuzzy.nExisting works discount this fact. In this article, we have presented an effective denoising procedure that uses fuzzy tool. The proposal uses type II fuzzy concept in setting the threshold. The need for Type II fuzzy instead of fuzzy is discussed in this article. The proposed algorithm is compared with four curreet popular wavmlet based procedures adopted in seismic denoising (noreal shrink, Shannon entropy shrink, Tsallis entropy shrink and visu shrink).