Multiple Window Time-Varying Spectrum Estimation

Metin Bayram and Richard Baraniuk
Rice University

mebay@ece.rice.edu, richb@rice.edu
www.dsp.rice.edu

We overview a new non-parametric method for estimating the
time-varying spectrum of a non-stationary random process.  Our method
extends Thomson's powerful multiple window spectrum estimation scheme
to the time-frequency and time-scale planes.  Unlike previous
extensions of Thomson's method, we identify and utilize optimally
concentrated Hermite window and Morse wavelet functions and develop a
statistical test for extracting chirping line components.  Examples on
synthetic and real-world data illustrate the superior performance of
the technique.

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To appear as a chapter in the Cambridge University Press Volume on the
Isaac Newton Institute program on Nonlinear and Nonstationary Signal
Analysis