Title :
Stability of some system identification techniques for underparameterized IIR adaptive filters
Author :
Fan, Hong ; Nayeri, Majid
Author_Institution :
Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
Abstract :
Stability for reduced-order identification is addressed. In particular, three system identification/adaptive filtering algorithms-the Steiglitz-McBride method (SMM), the recursive gradient method (RGM), and the instrumental variable method (IVM)-are revisited. It is shown that for some classes of reduced-order cases SMM and RGM yield stable solutions, whereas IVM can misbehave, although it has very good performance in sufficiently high-order cases. Thus it is concluded that no individual algorithm is superior, and that it is merely a tradeoff to choose one against the others in a specific application
Keywords :
adaptive filters; filtering and prediction theory; identification; matrix algebra; stability; Steiglitz-McBride method; adaptive filtering algorithms; instrumental variable method; recursive gradient method; reduced-order identification; stability; system identification techniques; three system identification; underparameterized IIR adaptive filters; Adaptive filters; Algorithm design and analysis; Asymptotic stability; Convergence; Delay; Filtering algorithms; Gradient methods; Postal services; System identification; Transfer functions;
Conference_Titel :
Circuits and Systems, 1989., IEEE International Symposium on
Conference_Location :
Portland, OR
DOI :
10.1109/ISCAS.1989.100704
