#TITLE_ALTERNATIVE#

• Main Author: FIRDAUS (NIM : 123 07 076), RUHUL
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/24128
• Institution: Institut Teknologi Bandung

Spectral analysis takes the important role in processing and interpretation seismic data. Earth is a non-stasionary medium so that seismic data has various <br /> <br /> <br /> <br /> <br /> frequency content during very short data span. For this kind of data, not every method can be used in order to analize the data. An approach is needed to represent local spectrum of the signal and to give rigth physical meaning. The existing methods have successfully mapped the spectrum on time-frequency plane, but those methods do not give good resolution. Novel contribution in signal processing to handle non-stasionary and nonlinear data is Empirical Mode Decomposition (EMD). <br /> <br /> <br /> <br /> <br /> EMD empirically decomposes any time-series data with highly stochastic behavior to a small group of sub-signal, called IMF (Intrinsic Mode Function). IMFs play two roles in data processing perspective, as individual filter and as an input to generate f-t representation using Hilbert transform (HT). The combination <br /> <br /> <br /> <br /> <br /> of EMD and HT is called Hilbert-Huang Transform (HHT). As a filter, IMF can be used together or individually to get the desired data structure. <br /> <br /> <br /> <br /> <br /> EMD implementation in denoising and detrending successfully enhances S/N ratio and improves the visibility of data structure. Complex attribute that <br /> <br /> <br /> <br /> <br /> applied to IMFs gives us new perspective in interpretation aspect. In the other hand, HHT mapped the spectrum with very high resolution of both temporal and <br /> <br /> <br /> <br /> <br /> frequency so that the uncertainty in spectral decomposition interpretation can be reduced.