Abstract
This paper proposes a normalized subband spline adaptive filter (SAF-NSAF) algorithm to solve the problem that linear subband adaptive filtering cannot identify nonlinear systems. The weight update of the proposed algorithm is conducted using the principle of minimum disturbance. Since a delayless structure is used in the proposed algorithm, a delay is not introduced into the update process. The effectiveness of the proposed algorithm is verified by simulations. Also, the mean and mean square stability of the proposed algorithm are evaluated using the principle of conservation of energy. The simulation results demonstrate that the performance of the proposed algorithm outperforms other cited nonlinear algorithms.
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Data Availability Statement
The datasets generated during and/or analyzed during the current study are available from the first author on reasonable request.
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Acknowledgements
This work was partially supported by the National Science Foundation of P. R. China under Grants 61671392, 62001528, 62071396, 61976237, and 61673404, the National Science Foundation of Henan Province under Grant 202300410517, the Research Award Fund for Outstanding Yong Teachers in Zhongyuan University of Technology (2018XQG09), the Key Scientific Research Projects in Colleges and Universities of Henan Province (20A120013, 21A120011). We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript.
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Wen, P., Zhang, J., Zhang, S. et al. Normalized Subband Spline Adaptive Filter: Algorithm Derivation and Analysis. Circuits Syst Signal Process 40, 2400–2418 (2021). https://doi.org/10.1007/s00034-020-01577-6
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DOI: https://doi.org/10.1007/s00034-020-01577-6