Shumin Hou and Yourong Li and Sanxing Zhao
Detecting the Nonlinearity in Time Series from Continuous Dynamic Systems Based on Delay Vector Variance Method
169 - 174
2007
1
2
International Journal of Mathematical and Computational Sciences
https://publications.waset.org/pdf/8521
https://publications.waset.org/vol/2
World Academy of Science, Engineering and Technology
Much time series data is generally from continuous dynamic system. Firstly, this paper studies the detection of the nonlinearity of time series from continuous dynamics systems by applying the Phaserandomized surrogate algorithm. Then, the Delay Vector Variance (DVV) method is introduced into nonlinearity test. The results show that under the different sampling conditions, the opposite detection of nonlinearity is obtained via using traditional test statistics methods, which include the thirdorder autocovariance and the asymmetry due to time reversal. Whereas the DVV method can perform well on determining nonlinear of Lorenz signal. It indicates that the proposed method can describe the continuous dynamics signal effectively.
Open Science Index 2, 2007