In this paper, we propose a new inference procedure for understanding non-stationary processes, under the framework of evolutionary spectra developed by Priestley. Among various frameworks of modeling non-stationary processes, the distinguishing feature of the evolutionary spectra is its focus on the physical meaning of frequency. The classical estimate of the evolutionary spectral density is based on a double-window technique consisting of a short-time Fourier transform and a smoothing. However, smoothing is known to suffer from the so-called bias leakage problem. By incorporating Thomson's multitaper method that was originally designed for stationary processes, we propose an improved estimate of the evolutionary spectral density, and analyze its bias/variance/resolution tradeoff. As an application of the new estimate, we further propose a non-parametric rank-based stationarity test, and provide various experimental studies.
Bibliographical noteFunding Information:
Manuscript received February 24, 2018; revised September 26, 2018 and October 29, 2018; accepted November 26, 2018. Date of publication January 1, 2019; date of current version January 16, 2019. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. D. Robert Iskander. This work was supported by Defense Advanced Research Projects Agency (DARPA) under Grants W911NF-14-1-0508, W911NF-16-1-0561, and N66001-15-C-4028. (Corresponding author: Yu Xiang.) Y. Xiang is with the Electrical and Computer Engineering Department, University of Utah, Salt Lake City, UT 84112 USA (e-mail:,email@example.com).
© 2018 IEEE.
- Evolutionary spectra
- Multitaper method
- Non-stationary processes
- Spectral analysis
- Stationarity test