On-line identification of time-varying systems by nonparametric techniques

1 February 1982

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Automatic Control

Vol. 27 (1) , 228-230
https://doi.org/10.1109/tac.1982.1102833

Abstract

A nonparametric algorithm, based on orthogonal series, is proposed for real-time identification of nonstationary systems. It is proved that the algorithm converges in the mean-square sense. The convergence conditions are closely related to those in Dupac [2].

Keywords

TIME VARYING SYSTEMS
BIFURCATION
RESONANCE
EIGENVALUES AND EIGENFUNCTIONS
FEEDBACK
VECTORS
LINEAR SYSTEMS
CONTEXT MODELING
INSPECTION
JACOBIAN MATRICES

This publication has 3 references indexed in Scilit:

A note on stochastic approximation algorithms in system identification
IEEE Transactions on Automatic Control, 1972
A Dynamic Stochastic Approximation Method
The Annals of Mathematical Statistics, 1965
On a Stochastic Approximation Method
The Annals of Mathematical Statistics, 1954