An Insightful Overview of the Wiener Filter for System Identification
Efficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related optimizat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/17/7774 |
| _version_ | 1797521732046684160 |
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| author | Laura-Maria Dogariu Jacob Benesty Constantin Paleologu Silviu Ciochină |
| author_facet | Laura-Maria Dogariu Jacob Benesty Constantin Paleologu Silviu Ciochină |
| author_sort | Laura-Maria Dogariu |
| collection | DOAJ |
| description | Efficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related optimization problems. In this paper, new insights into the regularization of the Wiener filter are provided, which is a must in real-world scenarios. A proper regularization technique is of great importance, especially in challenging conditions, e.g., when operating in noisy environments and/or when only a low quantity of data is available for the estimation of the statistics. Different regularization methods are investigated in this paper, including several new solutions that fit very well for the identification of sparse and low-rank systems. Experimental results support the theoretical developments and indicate the efficiency of the proposed techniques. |
| first_indexed | 2024-03-10T08:17:03Z |
| format | Article |
| id | doaj.art-8cdd743bd84042f0942438e467ecd1bd |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T08:17:03Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8cdd743bd84042f0942438e467ecd1bd2023-11-22T10:16:11ZengMDPI AGApplied Sciences2076-34172021-08-011117777410.3390/app11177774An Insightful Overview of the Wiener Filter for System IdentificationLaura-Maria Dogariu0Jacob Benesty1Constantin Paleologu2Silviu Ciochină3Department of Telecommunications, University Politehnica of Bucharest, 1-3, Iuliu Maniu Blvd., 061071 Bucharest, RomaniaINRS-EMT, University of Quebec, 800 de la Gauchetiere Ouest, Suite 6900, Montreal, QC H5A 1K6, CanadaDepartment of Telecommunications, University Politehnica of Bucharest, 1-3, Iuliu Maniu Blvd., 061071 Bucharest, RomaniaDepartment of Telecommunications, University Politehnica of Bucharest, 1-3, Iuliu Maniu Blvd., 061071 Bucharest, RomaniaEfficiently solving a system identification problem represents an important step in numerous important applications. In this framework, some of the most popular solutions rely on the Wiener filter, which is widely used in practice. Moreover, it also represents a benchmark for other related optimization problems. In this paper, new insights into the regularization of the Wiener filter are provided, which is a must in real-world scenarios. A proper regularization technique is of great importance, especially in challenging conditions, e.g., when operating in noisy environments and/or when only a low quantity of data is available for the estimation of the statistics. Different regularization methods are investigated in this paper, including several new solutions that fit very well for the identification of sparse and low-rank systems. Experimental results support the theoretical developments and indicate the efficiency of the proposed techniques.https://www.mdpi.com/2076-3417/11/17/7774system identificationWiener filterregularizationsparsenesslow-rank systemsingular value decomposition |
| spellingShingle | Laura-Maria Dogariu Jacob Benesty Constantin Paleologu Silviu Ciochină An Insightful Overview of the Wiener Filter for System Identification Applied Sciences system identification Wiener filter regularization sparseness low-rank system singular value decomposition |
| title | An Insightful Overview of the Wiener Filter for System Identification |
| title_full | An Insightful Overview of the Wiener Filter for System Identification |
| title_fullStr | An Insightful Overview of the Wiener Filter for System Identification |
| title_full_unstemmed | An Insightful Overview of the Wiener Filter for System Identification |
| title_short | An Insightful Overview of the Wiener Filter for System Identification |
| title_sort | insightful overview of the wiener filter for system identification |
| topic | system identification Wiener filter regularization sparseness low-rank system singular value decomposition |
| url | https://www.mdpi.com/2076-3417/11/17/7774 |
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