Localized Adaptive Bounds for Online Approximation Based Control
Localized Adaptive Bounds for Online Approximation Based Control
复制标题
DOI：
10.1109/cdc.2005.1582253
复制
发表时间：
2005-12
期刊：
影响因子：
--
通讯作者：
Yuanyuan Zhao;J. Farrell
中科院分区：
文献类型：
--
作者：
Yuanyuan Zhao;J. Farrell
本文发展了新的方法，以适应边界逼近精度的方法，涉及局部遗忘的方法。现有的结果使用了全局遗忘。局部遗忘与全局遗忘的重要性在文本中得到了激发。这样的界限对于自组织逼近器是有用的，它可以通过在逼近误差界较大的区域中添加额外的逼近资源来调整基本元素N的数目。
This article develops new methods for adaptively bounding approximation accuracy with methods that involve localized forgetting. The existing results use global forgetting. The importance of local versus global forgetting is motivated in the text. Such bounds have utility for self-organizing approximators that could adjust the number of basis elements N by adding additional approximation resources in the regions where the approximation error bound is large.