Smoothed multiple taper spectral analysis and adaptive implementation

Author

Riedel, Kurt S. ; Sidorenko, Alexander

Author_Institution

Courant Inst. of Math. Sci., New York, NY, USA

fYear

1994

fDate

25-28 Oct 1994

Firstpage

464

Lastpage

467

Abstract

A hybrid estimator of the log-spectral density of a stationary time series is proposed. First, a multiple taper estimate is performed, followed by kernel smoothing the log-multitaper estimate. This procedure reduces the expected mean square error by ((π²)/4)^0.8 over simply smoothing the log tapered periodogram. The optimal number of tapers is O(N⁸(15/)). A data adaptive implementation of a variable bandwidth kernel smoother is given

Keywords

adaptive estimation; adaptive signal processing; optimisation; smoothing methods; spectral analysis; time series; adaptive implementation; data adaptive implementation; expected mean square error; hybrid estimator; kernel smoothing; log tapered periodogram; log-multitaper estimate; log-spectral density; optimal taper number; smoothed multiple taper spectral analysis; stationary time series; variable bandwidth kernel smoother; Bandwidth; Fourier transforms; Kernel; Matrix decomposition; Mean square error methods; Robustness; Smoothing methods; Spectral analysis; Statistics; Virtual colonoscopy;

fLanguage

English

Publisher

ieee

Conference_Titel

Time-Frequency and Time-Scale Analysis, 1994., Proceedings of the IEEE-SP International Symposium on

Conference_Location

Philadelphia, PA

Print_ISBN

0-7803-2127-8

Type

conf

DOI

10.1109/TFSA.1994.467313

Filename

467313