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• W1533595479 abstract "While the prediction of dielectric loss spectra (DLS) from molecular weight distributions (MWD) is relatively straightforward the inversion is known to be an intrinsically ill-posed problem with high sensitivity to measurement noise. We propose artificial neural networks to solve this problem in two steps: First, the measured DLS is approximated by a special basis function network (BFN), thus reducing the data considerably and inherently smoothing the spectra. Second, a group of simple feedforward networks is employed to estimate the parameters of another BFN. The output of this second BFN is the estimate of the MWD. A simulation demonstrates the performance of the new method." @default.
• W1533595479 created "2016-06-24" @default.
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• W1533595479 date "2001-09-01" @default.
• W1533595479 modified "2023-09-27" @default.
• W1533595479 title "Estimation of molecular weight distribution of CIS-polyisoprene melts from dielectric loss spectra using neural networks" @default.
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• W1533595479 doi "https://doi.org/10.23919/ecc.2001.7076443" @default.
• W1533595479 hasPublicationYear "2001" @default.
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