极限情况下多重估计的融合研究

Jiří Ajgl, O. Straka
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引用次数: 0

摘要

分散估计往往为了解的简单性而牺牲最优性,而在未知相关性下的融合中,采用最坏情况类型的最优性。本文研究了在特殊情况下的简单解与最优解之间的差距。也就是说,对于无限数量的估计和待估计状态的无限维,对称配置被考虑。在这些学术案例中,如果考虑到边界球的大小,最优解决方案比简单解决方案好不到10%。在实践中,可以预期的差距要小得多。
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A Study of Fusions of Multiple Estimates for Limit Cases
Decentralised estimation often sacrifices optimality for solution simplicity, while within the fusion under unknown correlation, a worst-case type of optimality is adopted. This paper studies the gap between the simple solution and the optimal one for special cases. Namely, symmetric configurations are considered for infinite number of estimates and also for infinite dimension of the state to be estimated. In these academic cases, the optimal solution is better than the simple one by low tens percent, if the size of circumscribing balls is considered. In practice, much lower gap can be expected.
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