On the stability and convergence of a sliding‐window variable‐regularization recursive‐least‐squares algorithm |
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| Authors: | Asad A Ali Jesse B Hoagg Magnus Mossberg Dennis S Bernstein |
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| Affiliation: | 1. Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI 48109, USA;2. Department of Mechanical Engineering, University of Kentucky, Lexington, KY 40506, USA;3. Department of Engineering and Physics, Karlstad University, SE‐65188 4. Karlstad, Sweden |
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| Abstract: | A sliding‐window variable‐regularization recursive‐least‐squares algorithm is derived, and its convergence properties, computational complexity, and numerical stability are analyzed. The algorithm operates on a finite data window and allows for time‐varying regularization in the weighting and the difference between estimates. Numerical examples are provided to compare the performance of this technique with the least mean squares and affine projection algorithms. Copyright © 2015 John Wiley & Sons, Ltd. |
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| Keywords: | variable regularization sliding‐window RLS digital signal processing |
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