Gap Filling of Precipitation Data by SSA - Singular Spectrum Analysis
نویسندگان
چکیده
منابع مشابه
Gap filling of solar wind data by singular spectrum analysis
[1] Observational data sets in space physics often contain instrumental and sampling errors, as well as large gaps. This is both an obstacle and an incentive for research, since continuous data sets are typically needed for model formulation and validation. For example, the latest global empirical models of Earth’s magnetic field are crucial for many space weather applications, and require time...
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Observational data sets in space physics often contain instrumental and 3 sampling errors, as well as large gaps. This is both an obstacle and an in-4 centive for research, since continuous data sets are typically needed for model 5 formulation and validation. For example, the latest global empirical mod-6 els of Earth's magnetic field are crucial for many space weather applications, 7 and requ...
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Singular spectrum analysis (SSA), a linear univariate and multivariate time series technique , is essentially principal component analysis (PCA) applied to the time series and additional copies of the time series lagged by 1 to K time steps. Neural network theory has meanwhile allowed PCA to be generalized to nonlinear PCA (NLPCA). In this paper, NLPCA is further extended to perform nonlinear S...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2016
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/759/1/012085