Adaptive Filters
Novel FxLMS Convergence Condition With Deterministic Reference
IEEE Transactions on Signal Processing
Corrections to `The LMS algorithm with delayed coefficientadaptation'
IEEE Transactions on Signal Processing
Stochastic Analysis of the FXLMS-Based Narrowband Active Noise Control System
IEEE Transactions on Audio, Speech, and Language Processing
On the convergence of real-time active noise control systems
Signal Processing
Adaptive filtering with bandwidth constraints in the feedback path
Signal Processing
| Hi-index | 0.08 |
In system identification when a secondary path follows the adaptive filter, the FxLMS algorithm is usually applied for updating the adaptive filter. Although several FxLMS convergence analyses have been conducted in detail, only a few have intended to derive a convergence condition. In fact, available FxLMS convergence conditions are only accurate for simplified cases with pure delay secondary paths or multi-sinusoidal input signals. This paper studies the FxLMS convergence behavior for moving average secondary paths and stochastic input signals. A novel model for predicting the FxLMS convergence behavior is developed. Based on this model, a necessary and sufficient condition for the convergence of the FxLMS is derived. Also, the condition leading to the fastest convergence is proposed. Compared to previously derived convergence conditions, the proposed condition applies to more general secondary paths. Results obtained from this study are found to correspond very well to those obtained from simulation experiments.