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Particle filtering algorithm has been applied to various fields due to its capacity to handle nonlinear/non-Gaussian dynamic problems. One crucial issue in particle filtering is the selection of the proposal distribution that generates the particles. In this paper, we give a novel strategy for selecting proposal distribution. Firstly, divide-conquer(More)
The measurement of molecular interactions with pathological protein aggregates, including amyloid fibrils, is of central importance in the context of the development of diagnostic and therapeutic strategies against protein misfolding disorders. Probing such interactions by conventional methods can, however, be challenging because of the supramolecular(More)
A mixture Kalman Particle Filter (MKPF) based options pricing method is proposed. The MKPF algorithm uses the unscented Kalman filter (UKF) and the extended Kalman filter (EKF) as proposal distribution to generate the importance sampling density. Each particle is firstly updated by the UKF and obtains a state estimation. Thereafter, this estimation is used(More)
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