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Stationarity and normality test for biomedical data

✍ Scribed by H. Sugimoto; N. Ishii; A. Iwata; N. Suzumura


Publisher
Elsevier Science
Year
1977
Weight
532 KB
Volume
7
Category
Article
ISSN
0010-468X

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✦ Synopsis


Biomedical data, such as EEG, EMG and neural impulse sequences, are regarded as the stochastic phenomena of biological systems, and the statistical properties of such time series are often examined. Most of the statistical analysis processed in the frequency and the time domain are based on the assumption that the time series is weakly stationary and normally distributed. Therefore, as the basis of the statistical analysis of the biomedical data, it is necessary to know whether they satisfy the conditions of weak stationarity and normality. However, impulse response and evoked potential biomedical data, are not regarded as the stationary time series. Therefore, other analysis is required. In this paper, the authors present four programs, TEST1, TEST2, TEST3 and TEST4, to examine above conditions. Furthermore, in order to clarify the characteristic of each program, the time series were generated by the computer and examined by the test programs.


πŸ“œ SIMILAR VOLUMES


On the stationarity and normality of the
✍ Hideyuki Sugimoto; Naohiro Ishii; Akira Iwata; Nobuo Suzumura; Takao Tomita πŸ“‚ Article πŸ“… 1978 πŸ› Elsevier Science βš– 624 KB

In this paper, we show techniques to examine the stationaxity and the normality of time series as well as results obtained by applying these techniques to EEG data during sleep stages. Many statistical analyses of the EEG data are based on the assumption that the EEG data axe stationary and normally

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