A periodogram-based test for weak stationarity and consistency between sections in time series

被引:7
作者
Halliday, D. M. [1 ]
Rosenberg, J. R. [2 ]
Rigas, A. [3 ]
Conway, B. A. [4 ]
机构
[1] Univ York, Dept Elect, York YO10 5DD, N Yorkshire, England
[2] Univ Glasgow, Div Neurosci & Biomed Syst, Glasgow G12 8QQ, Lanark, Scotland
[3] Democritus Univ Thrace, Dept Elect Engn, Komotini, Greece
[4] Univ Strathclyde, Bioengn Unit, Glasgow G4 0NW, Lanark, Scotland
基金
英国惠康基金;
关键词
Spectral analysis; Periodogram; Time series; Stationarity; EEG; EMG; PHYSIOLOGICAL TREMOR; MOTOR TASK; SYNCHRONIZATION; ELECTROMYOGRAMS; IDENTIFICATION; FREQUENCY; SPECTRUM; SIGNALS;
D O I
10.1016/j.jneumeth.2009.03.009
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
in one approach to spectral estimation, a sample record is broken into a number of disjoint sections, or data is collected over a number of discrete trials. Spectral parameters are formed by averaging periodograms across these discrete sections or trials. A key assumption in this approach is that of weak stationarity. This paper describes a simple test that checks if periodogram ordinates are consistent across sections as a means of assessing weak stationarity. The test is called the Periodogram Coefficient of Variation (PCOV) test, and is a frequency domain test based on a technique of spectral analysis. Application of the test is illustrated to both simulated and experimental data (EMC, physiological tremor, EEG). An additional role for the test as a useful tool in exploratory analysis of time series is highlighted. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:138 / 146
页数:9
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