Title :
Stochastic approximation algorithms and applications
Author :
Kubrusly, C.S. ; Gravier, J.
Author_Institution :
Pontificia Universidade Catolica do Rio de Janeiro, Brazil
Abstract :
This study presents the conditions of applicability of stochastic approximation algorithms that minimize a mean-square error criterion for identification of a linear discrete-time stationary system without dynamical numerator. The acceleration of the convergence is discussed. Then a tentative is outlined to overcome the previous requirement of states accessibility.
Keywords :
Acceleration; Approximation algorithms; Convergence; Probability density function; Signal processing; Stochastic processes; Stochastic systems; Upper bound; Vectors; White noise;
Conference_Titel :
Decision and Control including the 12th Symposium on Adaptive Processes, 1973 IEEE Conference on
Conference_Location :
San Diego, CA, USA
DOI :
10.1109/CDC.1973.269114
