scholarly journals Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function

Algorithms ◽  
2013 ◽  
Vol 6 (3) ◽  
pp. 407-429 ◽  
Author(s):  
Bhusana Premanode ◽  
Jumlong Vongprasert ◽  
Christofer Toumazou
Keyword(s):  
Time Series ◽  
Noise Reduction ◽  
Time Series Data ◽  
Intrinsic Mode Function ◽  
Nonstationary Time Series ◽  
Series Data ◽  
Mode Function

Noise reduction in chaotic time series data

Pramana ◽  
1999 ◽  
Vol 52 (1) ◽  
pp. 25-37 ◽  
Author(s):  
A. Bhowal ◽  
T. K. Roy
Keyword(s):  
Time Series ◽  
Noise Reduction ◽  
Time Series Data ◽  
Chaotic Time Series ◽  
Series Data

Multiple-channel Singular Spectrum Analysis-based noise reduction for MT data observed in Boso Peninsula, Japan

2021 ◽  
Author(s):  
Shu Kaneko ◽  
Katsumi Hattori ◽  
Toru Mogi ◽  
Chie Yoshino
Keyword(s):  
Time Series ◽  
Noise Reduction ◽  
Spectrum Analysis ◽  
Reduction Method ◽  
Time Series Data ◽  
Singular Spectrum Analysis ◽  
Series Data ◽  
Boso Peninsula ◽  
Singular Spectrum ◽  
Kanto Earthquake

<p>Off the coast of the Boso Peninsula, there is a triple junction of the Pacific Plate, the Philippine Sea Plate, and the North American Plate and the Boso Peninsula is one of the seismically active areas in Japan. There are also epicenter areas such as the 1703 Genroku Kanto Earthquake (M8.2), the 1923 Taisho Kanto Earthquake (M7.9), and the Boso Slow Slip which occurs every 6 years, which are geologically interesting places. To estimate the subsurface resistivity structure of the whole Boso area, Magnetotelluric (MT) survey with 41 sites (inter-sites distance of 7 km) has been conducted in 2014-2016, using U43 (12 sites, 1 Hz sampling ; Tierra Technica) and MTU-5, 5A, net (41 sites, 15, 150, and 2400 Hz sampling; Phoenix Geophysics). However, the Boso area is greatly affected by leak current from DC-driven trains, factories, and power lines, so the observed data are contaminated by artificial noises. When we tried to apply the conventional noise reduction method (e.g., remote reference (Gamble et al., 1979) and BIRRP (Chave and Thomson, 2004)) in frequency domain, the obtained MT sounding curve was not ideal. In particular, the phase between the periods of 20 and 400 sec was close to 0 degrees. It suggests that the method used is insufficient to reduce the near-field effect for the Boso data. Thus, we developed a new noise reduction method using MSSA (Multi-channel Singular Spectrum Analysis) as a pre-processing method in time domain.</p><p>The procedure is as follows;</p><p>(1) Decompose 6 component data (Hx, Hy, Ex, Ey, Hxr and Hyr: H and E means magnetic and electric field, respectively, x and y indicates NS and EW component, and r denotes the reference field observed at a quiet station) using MSSA into 6×M principal components (PCs).  Here, M shows the window length of MSSA.</p><p>(2) Check contribution and periods of each PC and eliminate the PCs which are corresponding to the longer periods of variation. That is “detrend” of the original data.</p><p>(3) Apply the second MSSA to the detrended time series data to separate signals and noises shorter than 400 sec.</p><p>(4) Calculating correlation coefficients between H and Hr and between E and Hr for each PC and select the PCs with higher correlation to reconstruct time series data to make MT analysis.</p><p>Then, we perform MT analysis by BIRRP to estimate apparent resistivity,</p><p>As a result, the coherences of H-Hr, and E-Hr were improved and the MT sounding curve became smoother than those results by the conventional noise reduction methods. This indicated that the effectiveness of the proposed noise reduction. However, further investigation in different periods and sites will be required.</p>

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