ARMA system identification based on second-order cyclostationarity

@article{citeulike:1781147, abstract = {Previous work has presented novel techniques that exploit cyclostationarity for channel identification in data communication systems. The present authors investigate the identifiability of linear time-invariant (LTI) ARMA systems based on second-order cyclic statistics. They present a parametric and a nonparametric method. The parametric method directly identifies the zeros and poles of ARMA channels with a mixed phase. The nonparametric method estimates the channel phase based on the cyclic spectra alone. They analyze the phase estimation error of the nonparametric method for finite dimensional ARMA channels. For specific, finite dimensional ARMA channels, an improved method is given, which combines the parametric method with the nonparametric method. Computer simulation illustrates the effectiveness of the methods in identifying ARMA system impulse responses}, author = {Li, Ye and Ding, Zhi }, booktitle = {Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on]}, citeulike-article-id = {1781147}, journal = {Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on]}, number = {12}, pages = {3483--3494}, posted-at = {2007-10-17 20:30:56}, priority = {2}, title = {ARMA system identification based on second-order cyclostationarity}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=340782}, volume = {42}, year = {1994} }

TY - JOUR ID - citeulike:1781147 L3 - citeulike-article-id:1781147 TI - ARMA system identification based on second-order cyclostationarity T2 - Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on] JF - Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on] VL - 42 IS - 12 SP - 3483 EP - 3494 N2 - Previous work has presented novel techniques that exploit cyclostationarity for channel identification in data communication systems. The present authors investigate the identifiability of linear time-invariant (LTI) ARMA systems based on second-order cyclic statistics. They present a parametric and a nonparametric method. The parametric method directly identifies the zeros and poles of ARMA channels with a mixed phase. The nonparametric method estimates the channel phase based on the cyclic spectra alone. They analyze the phase estimation error of the nonparametric method for finite dimensional ARMA channels. For specific, finite dimensional ARMA channels, an improved method is given, which combines the parametric method with the nonparametric method. Computer simulation illustrates the effectiveness of the methods in identifying ARMA system impulse responses AU - Li, Ye AU - Ding, Zhi PY - 1994/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=340782 ER -