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171.
172.
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
173.
基于物质平衡方程、产能方程和递减方程的结合,提出了定容气田开发规划的概算法.该法可用于预测地层压力、井底流动压力、井口流动压力和稳产年限.实际应用表明,本文提供的方法是实用有效的. 相似文献
174.
Compositional data occur as natural realizations of multivariate observations comprising element proportions of some whole
quantity. Such observations predominate in disciplines like geology, biology, ecology, economics and chemistry. Due to unit
sum constraint on compositional data, specialized statistical methods are required for analyzing these data. Dirichlet distributions
were originally used to study compositional data even though this family of distribution is not appropriate (see Aitchison,
1986) because of their extreme independence properties. Aitchison (1982) endeavored to provide a viable alternative to existing
methods by employing Logistic Normal distribution to analyze such constrained data. However this family does not include the
Dirichlet class and is therefore unable to address the issue of extreme independence. In this paper generalized Liouville
family is investigated to model compositional data which includes covariates. This class permits distributions that admit
negative or mixed correlation and also contains non-Dirichlet distributions with non-positive correlation and overcomes deficits
in the Dirichlet class. Semiparametric Bayesian methods are proposed to estimate the probability density. Predictive distributions
are used to assess performance of the model. The methods are illustrated on a real data set. 相似文献
175.
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
176.
基于约束优化的联想记忆模型学习算法 总被引:1,自引:1,他引:0
本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。 相似文献
177.
Terry WindeattAuthor Vitae 《Pattern recognition》2003,36(12):2743-2756
Various measures, such as Margin and Bias/Variance, have been proposed with the aim of gaining a better understanding of why Multiple Classifier Systems (MCS) perform as well as they do. While these measures provide different perspectives for MCS analysis, it is not clear how to use them for MCS design. In this paper a different measure based on a spectral representation is proposed for two-class problems. It incorporates terms representing positive and negative correlation of pairs of training patterns with respect to class labels. Experiments employing MLP base classifiers, in which parameters are fixed but systematically varied, demonstrate the sensitivity of the proposed measure to base classifier complexity. 相似文献
178.
多传感器检测是使用多种(或多个)传感器对同一被测对象进行广泛的测量。应用多传感器检测技术和多传感器数据溶合技术对车削加工中的零件外圆尺寸检测进行了实验研究,结果表明,多传感器检测技术能够满足现代检测技术对信息的精确要求,使得检测监控系统更加准确、可靠。 相似文献
179.
180.
The cross-spectral estimation methods are efficient in estimating the parameters of sinusoidal signals embedded in colored noise. But up to now, only FPT and cross-periodogram methods are used in this field, the modern auto-spectral estimation method is introduced into cross-spectral estimation in this paper, meanwhile the cross-correlation based Yule-Walker equation is proposed theoretically and the moment and singular-value decomposition (SVD)) algorithms for cross-spectral estimation have been developed. Finally, a numerical example is given for comparing the presented methods with the well-known Cadzow's SVD method. 相似文献