The need for accurate monitoring and analysis of sequential data arises in many scientic, industrial

and nancial problems. Although the Kalman lter is effective in the linear-Gaussian

case, new methods of dealing with sequential data are required with non-standard models.

Recently, there has been renewed interest in simulation-based techniques. The basic idea behind

these techniques is that the current state of knowledge is encapsulated in a representative

sample from the appropriate posterior distribution. As time goes on, the sample evolves and

adapts recursively in accordance with newly acquired data. We give a critical review of recent

developments, by reference to oil well monitoring, ion channel monitoring and tracking

problems, and propose some alternative algorithms that avoid the weaknesses of the current

methods.相关搜索： gauss
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