.png){kind=icon}
返回
Affine projection algorithm with selective projections
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2012.02.018.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In the affine projection adaptive filtering algorithm, convergence is sped up by increasing the projection order but with an unwelcome consequence of increased steady-state misalignment. To address this unfavorable compromise, we propose a new affine projection algorithm with selective projections. This algorithm adaptively changes the projection order according to the estimated variance of the filter output error. The error variance is estimated using exponential window averaging with a variable forgetting factor and a simple moving averaging technique. The input regressors are selected according to two different criteria to update the filter coefficients at each iteration. Simulations, carried out for different adaptive filtering applications, demonstrate that the new algorithm provides fast initial convergence and low steady-state misalignment without necessarily trading off one for the other in addition to a significant reduction in average computational complexity. (C) 2012 Elsevier B.V. All rights reserved.
Keyword:
Adaptive filtering
Affine projection algorithm
Selective projections
Error variance estimation
期刊
IF:
3.6
论文数:
10.0K
被引数:
1.7W
机构
引用论文
Predicting the suitable habitats of Elwendia persica in the Indian Himalayan Region (IHR)预测Elwendia persica在印度喜马拉雅地区（IHR）的适宜栖息地
PREAI
分享收藏An affine projection algorithm with a data-selective method of using the condition number.png)
SIGNAL PROCESSING
SIGNAL PROCESSINGIF3.6
PREAI
分享收藏Utilizing ChatGPT-4 for Providing Information on Periodontal Disease to Patients: A DISCERN Quality AnalysisCureus
OAAI
CureusIF0
OAAI分享收藏
查看更多内容