Title :
Extraction of almost periodic signals using cyclostationarity
Author :
Dandawaté, Amod V. ; Giannakis, Georgios B.
Author_Institution :
Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA, USA
Abstract :
Extraction of almost periodic signals from their noisy observations is accomplished by exploiting cyclostationarity. The additive noise is allowed to be generally cyclostationary with unknown distribution. Consistency of the proposed estimators is proved and their asymptotic properties are presented. Further, adaptive algorithms are employed for tracking possible time-variations in the parameters of the almost periodic signal. Finally, the proposed methods are tested via simulations
Keywords :
adaptive estimation; adaptive signal processing; higher order statistics; time-varying systems; tracking; adaptive algorithms; additive noise; almost periodic signals; asymptotic properties; cumulants; cyclostationarity; estimators; noisy observations; signal extraction; simulations; time-variations; tracking; unknown distribution; Adaptive algorithm; Additives; Artificial intelligence; Helicopters; Helium; Interference; Signal processing; Speech enhancement; Testing; Underwater vehicles;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389851
