结合贝叶斯网络和神经网络，提出了一种建立数据驱动型的动态线性回归系统模型的方法。

A new method was represented to model dynamic linear regression system driven by data, in which a bayesian network was combined with the RBF neural network.

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我的主要工作是把粒子滤波算法引人到非线性贝叶斯动态模型中来，对非线性模型进行了模拟。

My main work is applying the particle filter algorithm to random simulate the non-linear Bayesian dynamic models.

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对一类非线性贝叶斯动态模型进行了处理。

In this paper, a kind of Nonlinear Bayesian Dynamic Model is solved.

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