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| Study of the Surrogate Data Method for Nonlinearity of Time Series |
| Lei Min; Wang Zhizhong |
| Dept. of Biomedical Engineering Shanghai Jiaotong University Shanghai 200030 China |
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Abstract Currently, the surrogate data method has become a widely used method in testing nonlinearity of time series. However, for the null hypothesis of linearly autocorrelated Gaussian noise with the mean and variance of the raw data, the exiting FT algorithms of generating surrogate data can not reproduce "pure" frequencies very well. In this paper, the surrogate data method is studied and an improved FT algorithms is proposed. Using the proposed algorithm, the surrogate data sets have the same mean, variance and Fourier spectrum with
the original data. This FT algorithm is compared to the previous and proved feasible by using Guass series and chaos time series of the logistic system.
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Received: 09 May 1999
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2001, Vol. 23 
