DocumentCode
322043
Title
Adjacent errors of stochastic gradient algorithms under general error criteria
Author
Anant, Venkat ; Priemer, Roland
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
Volume
2
fYear
1997
fDate
3-6 Aug 1997
Firstpage
778
Abstract
This paper gives a method to distinguish between the transient and steady states of stochastic gradient algorithms under general error criteria using inequalities that exist among a set of output errors called adjacent errors. Based on these inequalities, a variable step size LMF algorithm is proposed which improves convergence and gives lower misadjustment
Keywords
encoding; filtering theory; identification; prediction theory; transient analysis; adjacent errors; convergence; error criteria; misadjustment; output errors; steady states; stochastic gradient algorithms; transient states; variable step size LMF algorithm; Computer errors; Convergence; Equations; Estimation error; Least squares approximation; Steady-state; Stochastic processes; Stochastic resonance; Stochastic systems; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Conference_Location
Sacramento, CA
Print_ISBN
0-7803-3694-1
Type
conf
DOI
10.1109/MWSCAS.1997.662190
Filename
662190
Link To Document