Title :
Polyspectral analysis of mixed processes and coupled harmonics
Author :
Zhou, Guotong ; Giannakis, Georgios B.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
5/1/1996 12:00:00 AM
Abstract :
Polyspectral analysis of processes with mixed spectra is considered, and scaled polyperiodograms are introduced to clarify issues related to stationarity, ergodicity, and suppression of additive stationary noise in harmonic retrieval problems. Spectral and polyspectral approaches are capable of retrieving (un)coupled harmonics, not only when the harmonics have constant amplitudes, but also when they are observed in nonzero mean multiplicative noise. Fourier series polyspectra and asymptotic properties of scaled polyperiodograms provide general tools for higher order analysis of time series with mixed spectra. A single record phase coupling detector is derived to obviate the assumption of independent multiple records required by existing methods. The novelties are illustrated by simulation examples
Keywords :
Fourier series; harmonic analysis; interference suppression; signal detection; spectral analysis; time series; Fourier series polyspectra; additive stationary noise suppression; asymptotic properties; constant amplitude harmonics; coupled harmonics; ergodicity; harmonic retrieval problems; higher order analysis; mixed processes; mixed spectra; nonzero mean multiplicative noise; polyspectral analysis; scaled polyperiodograms; simulation; single record phase coupling detector; spectral approach; stationarity; time series; Additive noise; Couplings; Fourier series; Harmonic analysis; Noise level; Phase detection; Phase frequency detector; Phase noise; Signal analysis; Time series analysis;
Journal_Title :
Information Theory, IEEE Transactions on