Abstract
Characteristics of the mean-square error surface in adaptive digital filters determine how well a gradient algorithm performs within a given filter structure, i.e., if the surface has steep slopes and contains local minima, a gradient algorithm will have difficulty reaching the global minimum. It is shown how different filter structures of an adaptive filter leads to a change in the characteristics of the corresponding error surface, and consequently, to a change in the corresponding convergence rate and minimum mean-square error.
Original language | English (US) |
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Pages (from-to) | 485-496 |
Number of pages | 12 |
Journal | IEEE Transactions on Circuits and Systems |
Volume | 36 |
Issue number | 4 |
DOIs | |
State | Published - Apr 1989 |
All Science Journal Classification (ASJC) codes
- Engineering(all)