Title :
An interpretable and converging set-membership algorithm
Author :
Nayeri, M. ; Liu, M.S. ; Deller, J.R.
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
Set membership (SM)-based techniques, with least square error overlay, suffer from a trade-off between interpretability and proof of convergence. The authors introduce a modified SM algorithm with ´forgetting´ covariance updating in conjunction with minimum volume data selecting strategy. The convergence properties of this algorithm and its resemblance to the stochastic approximation method are discussed.<>
Keywords :
convergence; least squares approximations; set theory; variational techniques; covariance updating; interpretability; least square error overlay; minimum volume data selecting strategy; proof of convergence; set-membership algorithm; stochastic approximation method;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
Conference_Location :
Minneapolis, MN, USA
Print_ISBN :
0-7803-7402-9
DOI :
10.1109/ICASSP.1993.319697
