随机过程在指定坐标下的最优截断
Optimal Truncation for Random Process in the Prespecified Coordinate
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摘要: 提出了随机激励下的一种模型降阶方法.在指定坐标下,选择使输出误差性能指标 最小的分量,并对输出矩阵作最优修正,指出了这种最优截断法的几何正交性,为降阶控制器 设计提供了基础.最后给出了一个可行算法和算例.Abstract: An optimal method to truncate the components of a stable random output process in the prespecified coordinate is presented in this paper, which is based on the performance criterion of output error. It is pointed out that this optimal truncaion is also a minimal orthogonal projection of the truncated components. Several properties for such truncation are introduced. A numerical example is given in the end.
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Key words:
- Model reduction /
- random component /
- optimal truncation /
- minimum orthogonalization
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