TY - JOUR
T1 - Time-frequency analysis of seismic data using synchrosqueezing three parameter wavelet transform
AU - Liu, Naihao
AU - Gao, Jinghuai
AU - Lv, Qi
N1 - Publisher Copyright:
© 2015 SEG.
PY - 2015
Y1 - 2015
N2 - High-quality time-frequency representation (TFR) is important for signal analysis. Due to the Heisenberg uncertainty principle, traditional time-frequency methods always lead to ambiguous TFR which has negative effect on signal analysis. In this paper, we introduce a sparse and invertible time-frequency analysis method called the synchrosqueezing three parameter wavelet transform (SSTPWT) using the three parameter wavelet (TPW), which is developed to improve the quality and readability of TFR by condensing it along the frequency axis. Numerical experiments on synthetic signals and real seismic data show its effectiveness.
AB - High-quality time-frequency representation (TFR) is important for signal analysis. Due to the Heisenberg uncertainty principle, traditional time-frequency methods always lead to ambiguous TFR which has negative effect on signal analysis. In this paper, we introduce a sparse and invertible time-frequency analysis method called the synchrosqueezing three parameter wavelet transform (SSTPWT) using the three parameter wavelet (TPW), which is developed to improve the quality and readability of TFR by condensing it along the frequency axis. Numerical experiments on synthetic signals and real seismic data show its effectiveness.
UR - https://www.scopus.com/pages/publications/84994444845
U2 - 10.1190/segam2015-5837537.1
DO - 10.1190/segam2015-5837537.1
M3 - 会议文章
AN - SCOPUS:84994444845
SN - 1052-3812
VL - 34
SP - 5117
EP - 5121
JO - SEG Technical Program Expanded Abstracts
JF - SEG Technical Program Expanded Abstracts
T2 - SEG New Orleans Annual Meeting, SEG 2015
Y2 - 18 October 2011 through 23 October 2011
ER -