Title :
Parametric methods of cyclic-polyspectrum estimation for AM signals
Author :
Cheng, Qiansheng ; Li, Hongwei
Author_Institution :
Dept. of Inf. Sci., Beijing Univ., China
Abstract :
Parametric methods of amplitude-modulated (AM) models are discussed using the cyclic statistics of signals. The parameter equations of AM mixed phase models are given in terms of any order cyclic-cumulants and moments. For non-minimum phase AR, MA and ARMA models, the parameter estimation based on parameter equations and cumulant-polyspectra formulas is presented respectively. All the strongly consistent single record estimators based algorithms are phase sensitive and insensitive to any stationary noise
Keywords :
amplitude modulation; autoregressive processes; higher order statistics; moving average processes; parameter estimation; spectral analysis; AM mixed phase models; AM signals; ARMA models; MA models; amplitude modulated models; cumulant polyspectra formulas; cyclic cumulants; cyclic moments; cyclic polyspectrum estimation; cyclic statistics; nonminimum phase AR models; parameter equations; parameter estimation; parametric methods; phase sensitive algorithms; single record estimators based algorithms; stationary noise; Additive noise; Amplitude estimation; Amplitude modulation; Equations; Information science; Mathematical model; Parameter estimation; Parametric statistics; Phase noise; Statistical distributions;
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Print_ISBN :
0-7803-2912-0
DOI :
10.1109/ICSIGP.1996.566860
