.png){kind=icon}
.png){kind=icon}
Return
Spline Versoria Prioritization Optimization Algorithm With Modified Adaptive Moment Estimation: Analysis and Comparison
.png){kind=icon}
PRE
AI
DOI：10.1109/TCSII.2023.3303365.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Spline prioritization optimization adaptive filter (SPOAF) based on maximum Versoria criterion (MVC), named SPOAF-MVC, is renowned for its excellent robustness and low steady-state error. However, there is still room for improvement in its convergence speed, and its mean-square performance analysis has not yet been implemented. In view of the above, this brief proposes a robust SPOAF based on a modified adaptive moment estimation (MAME) method, called SPOAF-MVC-MAME, and makes a detailed theoretical analysis of the algorithm's performance. Simulation results provide practical evidence that bolsters the theoretical analysis and verify the efficacy of our algorithm.
Keywords:
Adaptive moment estimation
nonlinear system identification
non-Gaussian noise
spline adaptive filter
Journal
I
IF:
4.9
Papers:
8.8K
Citations:
2.5W