Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications
Résumé
The paper explores the use of dynamic adaptation gain/step size (DAG) for improving the adaptation transient performance of variable step-size LMS (VS-LMS) adaptation algorithms. A generic form for the implementation of the DAG within the VS-LMS algorithms is provided. The properties of the VS-LMS algorithms using dynamic adaptation gain are discussed in detail. Stability issues in deterministic environment and convergence properties in stochastic environment are examined. A transient performance analysis is proposed. Criteria for the selection of the coefficients of the DAG filter are provided.
The potential of the VS-LMS adaptation algorithms using a DAG is then illustrated by simulation results (adaptive line enhancer, filter identification) and experimental results obtained on a relevant adaptive active noise attenuation system.
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