随机反应网络的投影滤波
Projection-based filtering for stochastic reaction networks
摘要：
这项研究涉及在线推理（即，滤波）对反应网络状态的影响，以噪声和部分测量为条件。推导状态的条件概率分布满足的方程的困难源于这样一个事实，即支配反应网络演化的主方程在分析上是难以处理的。线性噪声近似（LNA）技术，这是广泛使用的反应网络的分析，最近被应用于发展近似推理。在这里，我们应用投影方法来推导近似滤波器，并将它们与基于LNA的滤波器在滤波性能上进行数值比较。我们还对比了投影方法与矩封闭技术在近似随机反应网络的演变。
英文摘要：
This study concerns online inference (i.e., filtering) on the state of reaction networks, conditioned on noisy and partial measurements. The difficulty in deriving the equation that the conditional probability distribution of the state satisfies stems from the fact that the master equation, which governs the evolution of the reaction networks, is analytically intractable. The linear noise approximation (LNA) technique, which is widely used in the analysis of reaction networks, has recently been applied to develop approximate inference. Here, we apply the projection method to derive approximate filters, and compare them to a filter based on the LNA numerically in their filtering performance. We also contrast the projection method with moment-closure techniques in terms of approximating the evolution of stochastic reaction networks.
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