Particle methods for change detection, system identification, and control
Particle methods are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. The ability to compute the optimal filter is central to solving important problems in areas such as change detection, parameter estimation,...
| Huvudupphovsmän: | , , , |
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| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
2004
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