On comparing statistical and set-based methods in sensor data fusion
Gregory D. Hager, Sofija Engelson, S. Atiya
- 发表年份
- 2002
- 引用次数
- 19
摘要
The theoretical and practical considerations of two common sensor data fusion methodologies (set based and statistically based parameter estimation) are compared. Their convergence behavior for a variety of simulated problems is examined. Robot localization systems implemented using both methods are described, and their performance is compared. It is concluded that set-based methods have performance that sometimes exceeds that of statistical methods, although this result is highly problem-dependent. These problem dependencies are characterized.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991