Study of Robust Diffusion Recursive Least Squares Algorithms with Side Information for Networked Agents
This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. This algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent const...
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| Jazyk: | angličtina |
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Ithaca
Cornell University Library, arXiv.org
24.12.2018
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| ISSN: | 2331-8422 |
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| Abstract | This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. This algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent constraint on the squared norm of the intermediate estimate update at each node. With the help of side information, the constraint is recursively updated in a diffusion strategy. Moreover, a control strategy for resetting the constraint is also proposed to retain good tracking capability when the estimated parameters suddenly change. Simulations show the superiority of the proposed algorithm over previously reported techniques in various impulsive noise scenarios. |
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| AbstractList | This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. This algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent constraint on the squared norm of the intermediate estimate update at each node. With the help of side information, the constraint is recursively updated in a diffusion strategy. Moreover, a control strategy for resetting the constraint is also proposed to retain good tracking capability when the estimated parameters suddenly change. Simulations show the superiority of the proposed algorithm over previously reported techniques in various impulsive noise scenarios. |
| Author | de Lamare, R C Y Yu Zakharov, Y |
| Author_xml | – sequence: 1 fullname: Y Yu – sequence: 2 givenname: R surname: de Lamare middlename: C fullname: de Lamare, R C – sequence: 3 givenname: Y surname: Zakharov fullname: Zakharov, Y |
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| Copyright | 2018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| DOI | 10.48550/arxiv.1812.09985 |
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| Snippet | This work develops a robust diffusion recursive least squares algorithm to mitigate the performance degradation often experienced in networks of agents in the... |
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| SubjectTerms | Algorithms Computer simulation Diffusion Least squares Parameter estimation Performance degradation Time dependence |
| Title | Study of Robust Diffusion Recursive Least Squares Algorithms with Side Information for Networked Agents |
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