A Recursive Least-Squares with a Time-Varying Regularization Parameter
Recursive least-squares (RLS) algorithms are widely used in many applications, such as real-time signal processing, control and communications. In some applications, regularization of the least-squares provides robustness and enhances performance. Interestingly, updating the regularization parameter...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-02-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/4/2077 |
| _version_ | 1827657335379591168 |
|---|---|
| author | Maaz Mahadi Tarig Ballal Muhammad Moinuddin Ubaid M. Al-Saggaf |
| author_facet | Maaz Mahadi Tarig Ballal Muhammad Moinuddin Ubaid M. Al-Saggaf |
| author_sort | Maaz Mahadi |
| collection | DOAJ |
| description | Recursive least-squares (RLS) algorithms are widely used in many applications, such as real-time signal processing, control and communications. In some applications, regularization of the least-squares provides robustness and enhances performance. Interestingly, updating the regularization parameter as processing data continuously in time is a desirable strategy to improve performance in applications such as beamforming. While many of the presented works in the literature assume non-time-varying regularized RLS (RRLS) techniques, this paper deals with a time-varying RRLS as the parameter varies during the update. The paper proposes a novel and efficient technique that uses an approximate recursive formula, assuming a slight variation in the regularization parameter to provide a low-complexity update method. Simulation results illustrate the feasibility of the derived formula and the superiority of the time-varying RRLS strategy over the fixed one. |
| first_indexed | 2024-03-09T22:40:46Z |
| format | Article |
| id | doaj.art-956d2edfc9304cc298480e636cea5a66 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T22:40:46Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-956d2edfc9304cc298480e636cea5a662023-11-23T18:38:51ZengMDPI AGApplied Sciences2076-34172022-02-01124207710.3390/app12042077A Recursive Least-Squares with a Time-Varying Regularization ParameterMaaz Mahadi0Tarig Ballal1Muhammad Moinuddin2Ubaid M. Al-Saggaf3Center of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah 21589, Saudi ArabiaDivision of Computer, Electrical and Mathematical Sciences and Engineering (CEMSE), King Abdullah University of Science and Technology (KAUST), Jeddah 23955, Saudi ArabiaCenter of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah 21589, Saudi ArabiaCenter of Excellence in Intelligent Engineering Systems (CEIES), King Abdulaziz University, Jeddah 21589, Saudi ArabiaRecursive least-squares (RLS) algorithms are widely used in many applications, such as real-time signal processing, control and communications. In some applications, regularization of the least-squares provides robustness and enhances performance. Interestingly, updating the regularization parameter as processing data continuously in time is a desirable strategy to improve performance in applications such as beamforming. While many of the presented works in the literature assume non-time-varying regularized RLS (RRLS) techniques, this paper deals with a time-varying RRLS as the parameter varies during the update. The paper proposes a novel and efficient technique that uses an approximate recursive formula, assuming a slight variation in the regularization parameter to provide a low-complexity update method. Simulation results illustrate the feasibility of the derived formula and the superiority of the time-varying RRLS strategy over the fixed one.https://www.mdpi.com/2076-3417/12/4/2077recursive least-squares (RLS)tikhonov regularizationTaylor’s series |
| spellingShingle | Maaz Mahadi Tarig Ballal Muhammad Moinuddin Ubaid M. Al-Saggaf A Recursive Least-Squares with a Time-Varying Regularization Parameter Applied Sciences recursive least-squares (RLS) tikhonov regularization Taylor’s series |
| title | A Recursive Least-Squares with a Time-Varying Regularization Parameter |
| title_full | A Recursive Least-Squares with a Time-Varying Regularization Parameter |
| title_fullStr | A Recursive Least-Squares with a Time-Varying Regularization Parameter |
| title_full_unstemmed | A Recursive Least-Squares with a Time-Varying Regularization Parameter |
| title_short | A Recursive Least-Squares with a Time-Varying Regularization Parameter |
| title_sort | recursive least squares with a time varying regularization parameter |
| topic | recursive least-squares (RLS) tikhonov regularization Taylor’s series |
| url | https://www.mdpi.com/2076-3417/12/4/2077 |
| work_keys_str_mv | AT maazmahadi arecursiveleastsquareswithatimevaryingregularizationparameter AT tarigballal arecursiveleastsquareswithatimevaryingregularizationparameter AT muhammadmoinuddin arecursiveleastsquareswithatimevaryingregularizationparameter AT ubaidmalsaggaf arecursiveleastsquareswithatimevaryingregularizationparameter AT maazmahadi recursiveleastsquareswithatimevaryingregularizationparameter AT tarigballal recursiveleastsquareswithatimevaryingregularizationparameter AT muhammadmoinuddin recursiveleastsquareswithatimevaryingregularizationparameter AT ubaidmalsaggaf recursiveleastsquareswithatimevaryingregularizationparameter |