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Arbitrary-order Hilbert spectral analysis for time series possessing scaling statistics: a comparison study with detrended fluctuation analysis and wavelet leaders
Arbitrary-order Hilbert spectral analysis time series wavelet leaders
2011/8/5
Abstract: In this paper we present an extended version of Hilbert-Huang transform, namely arbitrary-order Hilbert spectral analysis, to characterize the scale-invariant properties of a time series dir...
Nonparametric model reconstruction for stochastic differential equation from discretely observed time-series data
Nonparametric model reconstruction stochastic differential equation discretely observed time-series data
2011/8/2
Abstract: We develop a scheme for estimating state-dependent drift and diffusion coefficients in a stochastic differential equation from a time-series data. There is no need to have any prior knowledg...
Point Processes Modeling of Time Series Exhibiting Power-Law Statistics
point processes 1/fnoise stochastic differentiale quations power-law distributions
2010/4/27
We consider stochastic point processes generating time series exhibiting power laws of spectrum and distribution density (Phys. Rev. E 71, 051105 (2005)) and apply them for modeling the trading activi...
Expectation-maximization analysis of spatial time series
Expectation-maximization analysis spatial time series
2009/11/2
Expectation maximization (EM) is used to estimate the parameters of a Gaussian Mixture Model for spatial time series data. The method is presented as an alternative and complement to Empirical Orthogo...
Nonlinear Time Series Prediction
Using Chaotic Neural Networks
neural network chaotic dynamics forecasting nonlinear time series
2007/8/15
2001Vol.35No.6pp.759-762DOI:
Nonlinear Time Series Prediction
Using Chaotic Neural Networks
LI Ke-Ping and CHEN Tian-Lun
Department of Physics, Nankai University, Tianji...
Discussion of Some Problems About Nonlinear Time Series Prediction Using ν-Support Vector Machine
ν-SVM nonlinear time series prediction
2007/8/15
2007Vol.48No.1pp.117-124DOI:
Discussion of Some Problems About Nonlinear Time Series Prediction Using ν-Support Vector Machine
GAO Cheng-Feng, CHEN Tian-Lun, and NAN Tian-Shi
...
Nonlinear Time Series Prediction Using LS-SVM with
Chaotic Mutation Evolutionary Programming for Parameter Optimization
nonlinear time series prediction least squares support
vector machine chaotic mutation evolutionary programming
2007/8/15
2006Vol.45No.4pp.641-646DOI:
Nonlinear Time Series Prediction Using LS-SVM with
Chaotic Mutation Evolutionary Programming for Parameter Optimization
XU Rui-Rui, CHEN Tian-Lun, an...
Nonlinear Time Series Forecast Using Radial Basis Function Neural Networks
neural network nonlinear time series
clustering
2007/8/15
2003Vol.40No.2pp.165-168DOI:
Nonlinear Time Series Forecast Using Radial Basis Function Neural Networks
ZHENG Xin and CHEN Tian-Lun
Institute of Physics, Nankai Universi...
Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine
least squares support vector machine nonlinear time series prediction clustering
2007/8/15
2005Vol.43No.6pp.1056-1060DOI:
Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine
XU Rui-Rui, BIAN Guo-Xing, GAO Chen-Feng, and CHEN Tian...
Phase Space Prediction of Chaotic Time Series with Nu-Support Vector
Machine Regression
chaotic time series phase space prediction support vector machines
2007/8/15
2005Vol.43No.1pp.102-106DOI:
Phase Space Prediction of Chaotic Time Series with Nu-Support Vector
Machine Regression
YE Mei-Ying1 and WANG Xiao-Dong2
1 College of Mathem...