.png){kind=icon}
Return
Combined-Sample Multiband-Structured Subband Filtering Algorithms
.png){kind=icon}
PRE
AI
DOI：10.1109/TASLP.2022.3156791.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper introduces two combined-sample multiband-structured subband adaptive filters (MSAFs). In the design, an adaptive convex combination scheme of two self-reliant multi-sampled MSAF (MS-MSAF) with different sampled periods is firstly developed, which leads to the so-called CTMS-MSAF algorithm. Secondly, based on an adaptive filter, the combined-sample MS-MSAF (CMS-MSAF) algorithm is proposed via designing a time-varying sampled period, which possesses lower computational complexity than the former. Then, the convergence behaviors of the CTMS-MSAF and CMS-MSAF algorithms are investigated using standard mean-square deviation analysis. Finally, the simulation study in the system identification and acoustic echo cancellation applications shows that at the same steady-state error, the CMS-MSAF method provides a faster convergence rate than the improved convex combination of two MSAFs, combined-step-size MSAF and CTMS-MSAF algorithms.
Keywords:
Convergence
Steady-state
Optimized production technology
Speech processing
Time-domain analysis
Echo cancellers
Prediction algorithms
Adaptive filter
combined-sample
mean-square behavior
subband algorithm
Journal
I
IF:
5.1
Papers:
2.6K
Citations:
1.1W
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSave
View more