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- W4385259849 abstract "The application of feature selection to fault diagnosis is presented. First, Filtered data identification algorithm is derived for controlled autoregressive autoregressive (CARAR) system in order to estimate the system parameters. The Proposed technique offers a high computational efficiency. These estimated parameters are referred as features and these features are not all have the same informative value. Next, features selection is carried out using principal components analysis. Finally, the simulation results demonstrate the value of the suggested procedures." @default.
- W4385259849 created "2023-07-26" @default.
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- W4385259849 date "2023-06-29" @default.
- W4385259849 modified "2023-09-26" @default.
- W4385259849 title "Feature Selection for Fault Diagnosis Using Principal Component Analysis" @default.
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- W4385259849 doi "https://doi.org/10.1109/icest58410.2023.10187366" @default.
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