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- W2155809868 abstract "Affine model parametrizations using orthonormal basis functions have been widely used in system identification and adaptive signal processing. The main advantage of using orthonormal basis functions in a (generalized) orthonormal finite impulse response (FIR) filter lies in the possibility of incorporating prior knowledge of the system dynamics into the filter design and approximation process. As a result, more accurate and simplified models can be obtained with a limited number of basis functions. In this paper the linear parameter structure of a generalized FIR filter is used to formulate analytic solutions for model matching problems. Several construction methods of orthonormal basis functions are discussed and a case study using the generalized FIR filter to approximate the dynamics of an optimal feed-forward filter is presented" @default.
- W2155809868 created "2016-06-24" @default.
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- W2155809868 date "2006-01-01" @default.
- W2155809868 modified "2023-09-22" @default.
- W2155809868 title "Model Matching and Filter Design using Orthonormal Basis Functions" @default.
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- W2155809868 doi "https://doi.org/10.1109/cdc.2006.377643" @default.
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