DocumentCode
1891980
Title
A robust general normalised gradient descent algorithm
Author
Mandic, Danilo P. ; Obradovic, Dragan ; Kuh, Anthony
Author_Institution
Dept. of Electr. & Electron. Eng., Imperial Coll. London
fYear
2005
fDate
17-20 July 2005
Firstpage
133
Lastpage
136
Abstract
A modification of the generalised normalised gradient descent (GNGD) algorithm is introduced which caters for the steady state performance of the algorithm. This is achieved by combining the search-then-converge and gradient adaptive step size approaches. This way the proposed algorithm exhibits very fast convergence and small steady state error. Simulations on linear and nonlinear signals in prediction setting support the analysis
Keywords
adaptive signal processing; convergence of numerical methods; gradient methods; GNGD; general normalised gradient descent algorithm; gradient adaptive step size approach; linear signal; nonlinear signal; search-then-converge approach; steady state performance; Analytical models; Convergence; Educational institutions; Finite impulse response filter; Least squares approximation; Predictive models; Robustness; Signal analysis; Stability; Steady-state;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location
Novosibirsk
Print_ISBN
0-7803-9403-8
Type
conf
DOI
10.1109/SSP.2005.1628578
Filename
1628578
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