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• W2964476637 endingPage "103224" @default.
• W2964476637 startingPage "103224" @default.
• W2964476637 abstract "Streaming usually happens in systems with asymmetric nonlinearity. It is a dynamic phenomenon that the midpoint of the motion shifts away from the equilibrium point of the system. It is also an ultra-low-frequency process so that its observation often distorts because of signal acquisition limitations. Extensive studies have shown that the precision of parameter identification will drop greatly if this distortion is not accurately corrected. Motivated by the intention of enhancing the parameter identification’s precision via signal correction, the present paper proposes a novel approach called the orthonormal Legendre polynomial based denoising identification method (OLP-DIM). In this method, the distorted response is decomposed by the orthonormal Legendre polynomials. The polynomial coefficients corresponding to the distortion are treated as uncertain parameters and then jointly identified with the system parameters. Numerical and experimental examples with different responses show that the OLP-DIM returns parameters in excellent precision and, distinct from traditional parameter identification methods, accurately recovers the system’s streaming." @default.
• W2964476637 created "2019-08-13" @default.
• W2964476637 creator A5022270346 @default.
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• W2964476637 creator A5084477919 @default.
• W2964476637 date "2019-12-01" @default.
• W2964476637 modified "2023-10-14" @default.
• W2964476637 title "Denoising identification for nonlinear systems with distorted streaming" @default.
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• W2964476637 doi "https://doi.org/10.1016/j.ijnonlinmec.2019.07.009" @default.
• W2964476637 hasPublicationYear "2019" @default.
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