Bias‐compensated affine‐projection‐like algorithms with noisy input
A new class of bias‐compensated affine‐projection‐like (APL) algorithms is proposed, in which a bias‐compensation vector is derived to eliminate the bias caused by the noisy input. In addition, a new estimation method for the input noise variance is proposed which does not require the input–output n...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-04-01
|
| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/el.2015.3550 |
| Summary: | A new class of bias‐compensated affine‐projection‐like (APL) algorithms is proposed, in which a bias‐compensation vector is derived to eliminate the bias caused by the noisy input. In addition, a new estimation method for the input noise variance is proposed which does not require the input–output noise variance ratio in advance. Simulations in a system identification context show that the proposed algorithms achieve significant improvements in steady‐state misalignment as compared with the conventional APL algorithms. |
|---|---|
| ISSN: | 0013-5194 1350-911X |