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21.
Bayesian and Dempster-Shafer fusion 总被引:3,自引:0,他引:3
The Kalman Filter is traditionally viewed as a prediction-correction filtering algorithm. In this work we show that it can
be viewed as a Bayesian fusion algorithm and derive it using Bayesian arguments. We begin with an outline of Bayes theory,
using it to discuss well-known quantities such as priors, likelihood and posteriors, and we provide the basic Bayesian fusion
equation. We derive the Kalman Filter from this equation using a novel method to evaluate the Chapman-Kolmogorov prediction
integral. We then use the theory to fuse data from multiple sensors. Vying with this approach is the Dempster-Shafer theory,
which deals with measures of “belief”, and is based on the nonclassical idea of “mass” as opposed to probability. Although
these two measures look very similar, there are some differences. We point them out through outlining the ideas of the Dempster-Shafer
theory and presenting the basic Dempster-Shafer fusion equation. Finally we compare the two methods, and discuss the relative
merits and demerits using an illustrative example. 相似文献
22.
N. V. Khovanov 《Measurement Techniques》2007,50(3):255-258
A Bayesian model is proposed based on randomizing the systematic errors of the instruments. Conditions are identified under
which the randomization reduces the expected bias in estimating a measured quantity.
__________
Translated from Izmeritel’naya Tekhnika, No. 3, pp. 22–25, March, 2007. 相似文献
23.
Reconstruction of a discontinuous function from a few fourier coefficients using bayesian estimation
Alex Solomonoff 《Journal of scientific computing》1995,10(1):29-80
The goal of this paper is the application of spectral methods to the numerical solution of conservation law equations. Spectral methods furnish estimates of the firstn Fourier coefficients of the solution. But since the solutions of conservation law equations can have discontinuities, the estimate of the solution by summing the firstn terms of the Fourier series will haveO(1/n) error, even if the Fourier coefficients are known to high accuracy. But if the solution could be accurately reconstructed from its Fourier coefficients, spectral methods could be used effectively in these problems. A method for doing this is to assume a probability distribution for functions. Functions which are smooth away from the discontinuity are assumed to be likely, and those which are not smooth away from the discontinuity are assumed to be unlikely. Then a reconstruction algorithm is chosen by minimizing the expected error over all algorithms. It is possible to put the smoothness assumptions mentioned earlier into an infinite-dimensional Gaussian probability distribution, and then the minimum-error algorithm is well-known and fairly simple to construct and apply. If the Fourier coefficients of the reconstructed function are known exactly, then this approach gives very good results. But when used with Fourier coefficients obtained from a spectral approximation to Burgers' equation, the results were much less impressive, probably because the coefficients were not known very accurately. It is possible to construct filters that reconstruct a function using Legendre or Chebyshev coefficients for information instead Fourier coefficients. It is found that the performance of these filters is similar to the Fourier case. 相似文献
24.
25.
Necessary and sufficient conditions for the existence of a static state feedback that achieves noninteraction and internal
stability are obtained. This is accomplished by first characterizing the set of all controllability subspaces (distributions)
that can arise as solutions to the noninteracting control problem. This characterization is then used to identify a fixed
internal dynamics that is common to every noninteractive closed loop. The stability properties of this dynamics is shown to
be the key factor in the problem of achieving noninteracting control with internal stability. 相似文献
26.
27.
A stochastic model is proposed for a basic mechanism in the formation of uncertainties in physical quantity measurements.
__________
Translated from Izmeritel'naya Tekhnika, No. 1, pp. 12–17, January, 2006. 相似文献
28.
29.
We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real financial time series: the IBOVESPA stock index (São Paulo Stock Exchange). 相似文献
30.
Nowadays, the complex manufacturing processes have to be dynamically modelled and controlled to optimise the diagnosis and the maintenance policies. This article presents a methodology that will help developing Dynamic Object Oriented Bayesian Networks (DOOBNs) to formalise such complex dynamic models. The goal is to have a general reliability evaluation of a manufacturing process, from its implementation to its operating phase. The added value of this formalisation methodology consists in using the a priori knowledge of both the system's functioning and malfunctioning. Networks are built on principles of adaptability and integrate uncertainties on the relationships between causes and effects. Thus, the purpose is to evaluate, in terms of reliability, the impact of several decisions on the maintenance of the system. This methodology has been tested, in an industrial context, to model the reliability of a water (immersion) heater system. 相似文献