Title :
A finite-step global convergence algorithm for the parameter estimation of multichannel MA processes
Author :
Tong, Lang ; Inouye, Yujiro ; Liu, Ruey-wen
Author_Institution :
Dept. of Electr. & Comput. Eng., West Virginia Univ., Morgantown, WV, USA
fDate :
10/1/1992 12:00:00 AM
Abstract :
An iterative algorithm for the identification of multichannel moving average (MA) processes using higher-order statistics is proposed. It is shown that the algorithm has a finite-step global convergence property. Three multichannel MA models, including one nonminimum-phase MA model, are estimated by this algorithm with satisfactory performances
Keywords :
convergence; iterative methods; parameter estimation; signal processing; statistical analysis; finite-step global convergence algorithm; higher-order statistics; iterative algorithm; multichannel moving average processes; nonminimum-phase MA model; parameter estimation; Convergence; Ear; Higher order statistics; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Nonlinear equations; Parameter estimation; Phase estimation; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
