A. K. Cline and R. L. Renka. A storage-efficient method for construction of a thiessen triangulation. Rocky Mountain Journal of Mathematics, 14:119--  Home/Search Document Not in Database Summary Related Articles Check |
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IMACS/IEEE-SMC Multiconference CESA 96 - Symp. on.. - Learning Non-Linear Maps (Correct)
.... it can be shown that this triangulation minimizes the worst case approximation error that is obtained when linear interpolation of the node attributes is applied [3] The topological relations given by the Delaunay triangulation must be represented in an efficient datastructure; Cline and Renka [4] discuss various possibilties. Our implementation is based on a datastructure proposed by Lawson [5] which allows very fast access to the active nodes. For each simplex 2 Delta (n 1) words are stored, representing the indices of the n 1 nodes (vertices) and the indices of n 1 neighboring ....
A. K. Cline and R. L. Renka. A storage-efficient method for construction of a thiessen triangulation. Rocky Mountain Journal of Mathematics, 14:119--
Parametrization and Smooth Approximation of Surface.. - Michael Floater.. (1997) (40 citations) (Correct)
....of 25000, setting every internal u i = u i ; v i ) to be a point in the centre of D as an initial guess. The algorithm could be stopped after only a few hundred iterations and no instabilities were experienced. A suitable data structure for the triangulations is that proposed by Cline and Renka [4] for efficient storage of triangulations. Figure 6 shows a Delaunay triangulation of a set of 27 scattered data points in the plane. The points were mapped uniformly ( i;j = 1=d i for (i; j) 2 E) into the unit disc in Figure 7, placing the eight boundary nodes uniformly around the unit circle. In ....
Cline A. K., R. L. Renka, A storage-efficient method for construction of a Thiessen triangulation, Rocky Mount. J. Math. 14 (1984), 119--139.
Delaunay Networks for Modelling of Non-Linear Processes - Ullrich, Tolle (1996) (1 citation) (Correct)
....requirement can easily be met by positioning 2 n nodes as the vertices of a n dimensional embedding cube. A tool from computational geometry, the Delaunay triangulation of the scattered set of nodes, can be used to determine those simplices which actually contribute to the network s topology [2]. The network is built from Delaunay simplices which have the following property: Definition 2.1 A Simplex T k consisting of n 1 nodes located at positions s ki , i = 1; n 1 in IR n is a Delaunay simplex if and only if the embedding n dimensional hypersphere does not contain any ....
A. K. Cline and R. L. Renka. A storage-efficient method for construction of a thiessen triangulation. Rocky Mountain Journal of Mathematics, 14:119--139, 1984.
Modelling Nonlinear Characteristics using Hierarchical.. - Ullrich, Tolle (1997) (Correct)
....to avoid extrapolation. This is desirable because extrapolation generally leads to unreliable responses and the implementation of extrapolation routines involves computational overhead. A certain type of simplices which are particularly useful for function approximation are Delaunay simplices [5]. They are characterized by the empty circle property: Definition 2.1 A simplex T i consisting of n 1 nodes in IR n is a Delaunay simplex if and only if its embedding n dimensional hypersphere does not contain any other node of the network. Figure 2 (left) illustrates this definition for a ....
A. K. Cline and R. L. Renka. A storage-efficient method for construction of a thiessen triangulation. Rocky Mountain Journal of Mathematics, 14:119--139, 1984.
Siscat Reference Manual - Volume Iii Explicit (Correct)
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A. K. Cline and R. J. Renka, A storage-efficient method for construction of a thiessen triangulation. Rocky Mountain J. Math., 14:119--140, 1984.
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