Title :
Adaptive IIR system identification with fixed pole location via balanced model truncation
Author :
Pasquato, L. ; Kale, I. ; Cain, G.D.
Author_Institution :
Div. of Electron. Syst., Westminster Univ., London, UK
Abstract :
Adaptive filtering theory reveals obstacles concerning convergence and stability in the IIR situation. Here we show how to completely avoid the stability problem while also reducing convergence difficulties-all by the application of the Balanced Model Truncation (BMT) algorithm. The specific case of system identification is investigated
Keywords :
IIR filters; adaptive filters; circuit analysis computing; circuit stability; identification; adaptive IIR system identification; balanced model truncation; balanced model truncation algorithm; convergence; fixed pole location; obstacles; stability; system identification; Adaptive filters; Adaptive systems; Convergence; Finite impulse response filter; IIR filters; Least squares approximation; Robustness; Stability; System identification; Working environment noise;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. Sensing, Processing, Networking., IEEE
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-7803-3747-6
DOI :
10.1109/IMTC.1997.603936
