Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866929320631468032 |
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| author | Landau, Ioan Doré Bismor, Dariusz Airimitoaie, Tudor-Bogdan Vau, Bernard Buche, Gabriel |
| author_facet | Landau, Ioan Doré Bismor, Dariusz Airimitoaie, Tudor-Bogdan Vau, Bernard Buche, Gabriel |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_12672 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications Landau, Ioan Doré Bismor, Dariusz Airimitoaie, Tudor-Bogdan Vau, Bernard Buche, Gabriel Optimization and Control 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. |
| title | Speeding up VSLMS adaptation algorithms using dynamic adaptation gain: Analysis and Applications |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2404.12672 |