Abstract
A gradient based variable forgetting factor (GVFF) RLS lattice (RLSL) algorithm is introduced in this paper. The steepest descent approach is used to control the forgetting factor which is based on the dynamic equation of the gradient of the mean square error. Compared with the standard RLSL algorithm, GVFF-RLSL algorithm gives fast tracking with a small mean square model error and its performance is not degraded much even in low signal-to-noise ratios (SNR) for time varying systems. Copyright © 2003 by The Institute of Electrical and Electronics Engineers, Inc.
| Original language | English |
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| Title of host publication | Proceedings of the International Joint Conference on Neural Networks 2003 |
| Place of Publication | USA |
| Publisher | IEEE |
| Pages | 1168-1172 |
| Volume | 2 |
| ISBN (Print) | 0780378989 |
| DOIs | |
| Publication status | Published - 2003 |