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- W1569204631 abstract "Most of chem. sensors do suffering aging or poisoning problems over the long period of time. This drift causes electronic nose to predict odors difficulty after some period of time. The authors applied an adaptive Gaussian radial basis function (RBF) network based on the Stochastic Gradient (SG) method to perform for drift compensation. The centers and widths of RBF Network were finely tuned by SG method and wts. between hidden and output layer were calcd. by Singular value decompn. (SVD) to minimize prediction error in iterative learning stage. The adaptive RBF network showed good odor prediction performance after some period of time, even if the sensors suffer from aging and poisoning problems. It was confirmed by exptl. trails. [on SciFinder (R)]" @default.
- W1569204631 created "2016-06-24" @default.
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- W1569204631 date "2001-01-01" @default.
- W1569204631 modified "2023-09-22" @default.
- W1569204631 title "Application of adaptive RBF network for odour classification under drift effect using conducting polymer sensor array" @default.
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