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• W4322761710 abstract "A novel recurrent model called nonlinear autoregressive spline neural filter (NARSNF) is introduced in this paper. Due to its unique spline nonlinear output autoregressive structure, NARSNF exhibits better fitting ability than IIR-spline adaptive filter (IIR-SAF) in identifying nonlinear dynamic systems with output autoregression. Correspondingly, the real-time recurrent learning algorithm based on NARSNF is derived and the Lyapunov stability analysis of learning rates is also provided. Moreover, the NARSNF and bilinear NARSNF (BNARSNF) are proposed to handle compensation of acoustic feedback for nonlinear active noise control (NANC). At last, simulation results in the context of nonlinear dynamic system identification and NANC verify the effectiveness of the proposed models." @default.
• W4322761710 created "2023-03-03" @default.
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• W4322761710 date "2023-07-01" @default.
• W4322761710 modified "2023-09-27" @default.
• W4322761710 title "Nonlinear autoregressive spline neural filter and its application" @default.
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• W4322761710 doi "https://doi.org/10.1016/j.sigpro.2023.109000" @default.
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