2009
DOI: 10.1088/1742-2132/6/2/009
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Noise reduction by support vector regression with a Ricker wavelet kernel

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Cited by 5 publications
(2 citation statements)
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“…3,6,7 With regards to the technology based on spectrophotometry, many scientists use the UV-Vis absorbance at 254 nm wavelength as an input, due to the strong linear correlation with organic content and the absorbance at 254 nm under ideal conditions. 8 However, the UV-Vis absorbance at 254 nm can easily be inuenced by scattering, which can cause a signicant deviation and raise the degree of uncertainty in the obtained result. Thus, some scientists have considered UV-Vis absorbance at other wavelengths, such as 350 and 465 nm, as a second input to establish an improved measurement model in order to compensate the inuence from scattering.…”
Section: Introductionmentioning
confidence: 99%
“…3,6,7 With regards to the technology based on spectrophotometry, many scientists use the UV-Vis absorbance at 254 nm wavelength as an input, due to the strong linear correlation with organic content and the absorbance at 254 nm under ideal conditions. 8 However, the UV-Vis absorbance at 254 nm can easily be inuenced by scattering, which can cause a signicant deviation and raise the degree of uncertainty in the obtained result. Thus, some scientists have considered UV-Vis absorbance at other wavelengths, such as 350 and 465 nm, as a second input to establish an improved measurement model in order to compensate the inuence from scattering.…”
Section: Introductionmentioning
confidence: 99%
“…In Northeast China, countermeasures are hard to apply due to the complex geology (which leads to complicated coherent noise), and to severe winter storms for more than 5 months a year (which leads primarily to powerful random noise). Therefore, many available methods (Deng et al, 2010(Deng et al, , 2011Naghizadeh and Sacchi, 2009;Satish and Nazneen, 2003) do not produce satisfactory results. Time-frequency peak filtering (TFPF) and its extension in the temporal and spatial domain would be a good choice (Lin et al, 2007) to eliminate the strong random noise.…”
Section: Introductionmentioning
confidence: 99%