Title :
Uniqueness of MSOE estimates in IIR adaptive filtering; a search for necessary conditions
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
In adaptive IIR (infinite impulse response) filtering, gradient search techniques minimize the mean-square output error (MSOE). The uniqueness of the minimum MSOE estimate for exactly matching adaptive filters is a necessary condition for global convergence of these algorithms. Although the existence of stable degenerated solutions is sufficient for the existence of local minima, it is shown by an example not to be a necessary condition, this uniqueness is also guaranteed if T. Soderstrom´s (1985) condition, nb-ne+1⩾0, is met when the input is white. It is proved that nb-nc+2⩾0 is a weaker sufficient condition for exactly matching models. In fact, this serves as the weakest sufficient condition
Keywords :
adaptive filters; error analysis; filtering and prediction theory; IIR adaptive filtering; gradient search techniques; infinite impulse response; matching adaptive filters; matching models; mean-square output error; Adaptive filters; Adaptive signal processing; Additive noise; Equations; Filtering; IIR filters; Laboratories; Signal processing algorithms; Sufficient conditions; White noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Conference_Location :
Glasgow
DOI :
10.1109/ICASSP.1989.266611