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- W2279671102 abstract "| This paper investigates the use of prior information in the structure selection of RBF network models, which are usually obtained by the same way regardless of the available information about the underlying system. The paper shows how the eigenvalue function is mapped in RBF network models, developing mathematical expressions relating this function to signals and model coeAEcients. The line of reasoning used in the study is applied in the derivation of a simple structure constraint that guarantees a model with eigenvalues that do not vary with the operating point. The scheme is applied to examples consisting of simulated and real data. As a result, models with better dynamic and steady-state performances are obtained, as assessed by free-run predictions and by the recovering of system static nonlinearity. Key Words| RBF network models; prior information; structure selection." @default.
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- W2279671102 date "2002-01-01" @default.
- W2279671102 modified "2023-09-26" @default.
- W2279671102 title "Using prior information in the structure selection of RBF network models" @default.
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