Harmonics in multiplicative and additive noise: parameterestimation using cyclic statistics

Authors:
G.B. Giannakis;Guotong Zhou
Affiliations:
Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA;-
Venue:
IEEE Transactions on Signal Processing
Year:
1995

Citing 0
Cited 6

Cyclostationarity: half a century of research

Signal Processing
Bibliography on cyclostationarity

Signal Processing
Estimation of the number of harmonics in multiplicative and additive noise

Signal Processing
Blind identification of second order volterra systemswith complex random inputs using higher order cumulants

IEEE Transactions on Signal Processing
Two-dimensional harmonic retrieval in correlative noise based on genetic algorithm

EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
Detecting the number of 2-D harmonics in multiplicative and additive noise using enhanced matrix

Digital Signal Processing

Quantified Score

Hi-index	35.69

Visualization

Abstract

The problem of concern here is parameter estimation of harmonics in the presence of multiplicative and additive noise. Cyclic statistics are employed to estimate the frequencies and phases, after which the time series is demodulated and cumulants of the noise processes are estimated. The latter are then supplied to linear or nonlinear cumulant-based algorithms to identify ARMA model parameters for the noises. Cyclic statistics and higher order spectra-based approaches are shown to yield the same frequency estimates. Simulation examples illustrate the algorithms