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Decomposition-Based Recursive Least Squares Algorithm for Wiener Nonlinear Feedback FIR-MA Systems Using the Filtering Theory

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Abstract

A decomposition-based recursive least squares algorithm is developed for Wiener nonlinear systems described by finite impulse response moving average models. After transferring a finite impulse response moving average (FIR-MA) model to a controlled autoregressive model, we compute the parameters by combining the decomposition principle and the least squares method and using the filtering idea. The simulation results validate the proposed algorithm.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (Nos. 61174032, 61202473), the Doctoral Foundation of Higher Education Priority Fields of Scientific Research (No. 20110093130001), the Scientific Research Foundation of Jiangnan University (No. 1252050205135110), and by the PAPD of Jiangsu Higher Education Institutions.

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  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi , 214122, People’s Republic of China

    Ziyun Wang, Yan Wang & Zhicheng Ji

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  1. Ziyun Wang
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  2. Yan Wang
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  3. Zhicheng Ji
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Correspondence to Yan Wang.

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Wang, Z., Wang, Y. & Ji, Z. Decomposition-Based Recursive Least Squares Algorithm for Wiener Nonlinear Feedback FIR-MA Systems Using the Filtering Theory. Circuits Syst Signal Process 33, 3649–3662 (2014). https://doi.org/10.1007/s00034-014-9806-5

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  • DOI: https://doi.org/10.1007/s00034-014-9806-5

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