Brown, M. and Ullrich, T.
Comparison of Node Insertion Algorithms for Delaunay Networks.
2nd Mathematical Modelling Conference (MathMod)
Full text not available from this repository.
This paper compares three different node insertion strategies which can be used to incrementally construct Delaunay triangulation models. Delaunay networks may be used to efficiently store low dimensional nonlinear models, and can therefore be used in a wide range of real-time applications. However, there are no direct node selection methods, and it can be shown that the network's generalisation abilities are strongly affected by the triangular partitioning of the input space. The three iterative, constructive node insertion algorithms (maximum error, local weighted error and one-step-ahead optimal search) are compared using two data sets, and conclusions are drawn about the quality of the extracted triangulation and the algorithms' computational costs.
Actions (login required)