IncepTCN: A new deep temporal convolutional network combined with dictionary learning for strong cultural noise elimination of controlled-source electromagnetic …
When the controlled-source electromagnetic (CSEM) data are contaminated by intense
cultural noise and the signal-to-noise ratio (S/N) is lower than 0 dB, the existing denoising …
cultural noise and the signal-to-noise ratio (S/N) is lower than 0 dB, the existing denoising …
Dictionary learning and shift-invariant sparse coding denoising for controlled-source electromagnetic data combined with complementary ensemble empirical mode …
Controlled-source electromagnetic (CSEM) data recorded in industrialized areas are
inevitably contaminated by strong cultural noise. Traditional noise attenuation methods are …
inevitably contaminated by strong cultural noise. Traditional noise attenuation methods are …
Noise attenuation for csem data via deep residual denoising convolutional neural network and shift-invariant sparse coding
X Wang, X Bai, G Li, L Sun, H Ye, T Tong - Remote Sensing, 2023 - mdpi.com
To overcome the interference of noise on the exploration effectiveness of the controlled-
source electromagnetic method (CSEM), we improved the deep learning algorithm by …
source electromagnetic method (CSEM), we improved the deep learning algorithm by …
De-noising low-frequency magnetotelluric data using mathematical morphology filtering and sparse representation
De-noising the magnetotelluric (MT) data using the conventional time-series editing
methods is at the risk of losing low-frequency signals, especially the signal below 1 Hz. To …
methods is at the risk of losing low-frequency signals, especially the signal below 1 Hz. To …
Denoising of magnetotelluric data using K‐SVD dictionary training
J Li, Y Peng, J Tang, Y Li - Geophysical Prospecting, 2021 - earthdoc.org
Magnetotelluric is one of the mainstream exploration geophysical methods, which plays a
vital role in studying deep geological structures and finding deep hidden blind ore bodies …
vital role in studying deep geological structures and finding deep hidden blind ore bodies …
Extraction of high-frequency SSVEP for BCI control using iterative filtering based empirical mode decomposition
CC Hsu, CL Yeh, WK Lee, HT Hsu, KK Shyu… - … Signal Processing and …, 2020 - Elsevier
Steady-state visual evoked potential (SSVEP) has been regarded as an efficient way to
design a brain computer interface (BCI). Most SSVEP-based BCIs utilize visual stimuli with …
design a brain computer interface (BCI). Most SSVEP-based BCIs utilize visual stimuli with …
[HTML][HTML] 基于灰色判别准则和有理函数滤波的伪随机电磁数据去噪
陈超健， 蒋奇云， 莫丹， 李广， 周峰 - 地球物理学报, 2019 - html.rhhz.net
为压制伪随机多频电磁信号中的强干扰, 提高数据质量, 本文提出一种基于灰色判别准则和有理
函数滤波的数据处理方法. 首先通过灰色判别准则剔除各个频点频谱数据中的明显异常值 …
函数滤波的数据处理方法. 首先通过灰色判别准则剔除各个频点频谱数据中的明显异常值 …
Damage identification for pile foundation in high-piled wharf using composite energy factors driven by dynamic response under wave impact excitation
C Li, Q Wang, R Zhu, Y Zhu, Y Hu - Ocean Engineering, 2024 - Elsevier
Exploring dynamic response-based damage identification under wave excitation is
important for establishing a health monitoring system. In our previous study, we analyzed the …
important for establishing a health monitoring system. In our previous study, we analyzed the …
Robust CSEM data processing by unsupervised machine learning
G Li, Z He, J Deng, J Tang, Y Fu, X Liu… - Journal of Applied …, 2021 - Elsevier
The ambient noise in controlled-source electromagnetic (CSEM) data seriously affects the
accuracy and reliability of the exploration result. Traditional correlation-based data selection …
accuracy and reliability of the exploration result. Traditional correlation-based data selection …
Magnetotelluric signal-noise separation method based on SVM–CEEMDWT
J Li, J Cai, JT Tang, G Li, X Zhang, ZM Xu - Applied Geophysics, 2019 - Springer
To better retain useful weak low-frequency magnetotelluric (MT) signals with strong
interference during MT data processing, we propose a SVM-CEEMDWT based MT data …
interference during MT data processing, we propose a SVM-CEEMDWT based MT data …