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- W4252594784 abstract "The estimation of time-varying aerosol size distributions on the basis of differential mobility particle sizer measurements is a dynamical inverse problem with a non-linear/non-Gaussian state space model. A sequential Monte Carlo approach for determining approximations for the state estimates is proposed. The vapour pressure, which is difficult to measure accurately, is here taken as an unknown state variable instead of assuming an approximate average value. Two simulation studies are carried out and the results are also compared with those obtained by using the extended Kalman filter which employs sequential Gaussian approximations based on the same state space model. The results show that in some cases the extended Kalman filter is a feasible approach while there are also evolution models for which the linear/Gaussian approximation is not sufficient." @default.
- W4252594784 created "2022-05-12" @default.
- W4252594784 creator A5082567966 @default.
- W4252594784 date "2004-05-01" @default.
- W4252594784 modified "2023-09-25" @default.
- W4252594784 title "Sequential Monte Carlo estimation of aerosol size distributions" @default.
- W4252594784 doi "https://doi.org/10.1016/s0167-9473(04)00085-4" @default.
- W4252594784 hasPublicationYear "2004" @default.
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