Abstract
A new two-dimensional (2D) sample-based conjugate gradient (SCO) algorithm is developed for adaptive filtering. This algorithm is based on the conjugate gradient method of optimization and therefore has a fast convergence characteristic. The SCG is computationally simpler than the recursive least squares (RLS) algorithm. The SCG algorithm with the equation-error and output-error methods is investigated for application in image restoration. Simulation results show that the new algorithm significantly outperforms existing algorithms in the restoration of noisy images.
Original language | English (US) |
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Pages (from-to) | 197-206 |
Number of pages | 10 |
Journal | Circuits, Systems, and Signal Processing |
Volume | 16 |
Issue number | 2 |
DOIs | |
State | Published - 1997 |
Externally published | Yes |
ASJC Scopus subject areas
- Signal Processing
- Applied Mathematics