Estimation of aerosol particle number distributions with Kalman Filtering – Part 1: Theory, general aspects and statistical validity
نویسندگان
چکیده
منابع مشابه
Estimating Particle Number Size Distributions from Multi-instrument Observations with Kalman Filtering
Atmospheric aerosol particles have several important effects on the environment and human society. The exact impact of aerosol particles is largely determined by their particle size distributions. However, no single instrument is able to measure the whole range of the particle size distribution. Estimating a particle size distribution from multiple simultaneous measurements remains a challenge ...
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For linear dynamic systems with white process and measurement noise, the Kalman ̄lter is known to be the minimum variance linear state estimator. In the case that the random quantities are Gaussian, then the Kalman ̄lter is the minimim variance state estimator. However, in the application of Kalman ̄lters known signal information is often either ignored or dealt with heuristically. For instance...
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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 strategy is used, in which the particles used...
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We develop a physical analogy for the Kalman-Bucy filter, in which the partially observed signal describes a statistical mechanical system interacting with a heat bath. The ‘universe’ comprising this system and the heat bath obeys a non-decrease law of entropy similar to the Second Law of Thermodynamics. However, this law can be violated in the presence of partial observations. Like Maxwell’s d...
متن کاملBiological aerosol particle concentrations and size distributions
Introduction Conclusions References
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ژورنال
عنوان ژورنال: Atmospheric Chemistry and Physics
سال: 2012
ISSN: 1680-7324
DOI: 10.5194/acp-12-11767-2012