Probability density update for a distributed system based on unnormalized local densities in the continuous-discrete case

C. McCullough
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Abstract

Results have been published that give the conditional probability density update for a distributed nonlinear stochastic system that is based on the conditional density updates for the local estimators. However, the local densities are required to be solutions to nonlinear equations, which are unsolvable in the general case. A formulation that uses unnormalized local densities, which are more tractable, and yet produces the same normalized density for the global system as the previous method is given. This new result is applicable to a much wider variety of problems than the former due to the larger body of problems for which unnormalized densities are available.<>
连续离散情况下基于非归一化局部密度的分布式系统概率密度更新
基于局部估计量的条件密度更新,给出了分布非线性随机系统的条件概率密度更新。然而,局部密度要求是非线性方程的解,这在一般情况下是不可解的。本文给出了一种使用非归一化局部密度的公式,这种方法更容易处理,但对于全局系统产生与前一种方法相同的归一化密度。这个新结果比前者适用于更广泛的问题,因为有更多的问题可以得到非归一化密度。
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