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|Title: ||Constrained visualization using the Shepard Interpolation Family|
|Author: ||Brodlie, K. W.|
Asim, M. R.
|Publisher: ||Lincoln University. Applied Computing, Mathematics and Statistics Group.|
|Series/Report no.: ||Research report (Lincoln University (Canterbury, N.Z.). Applied Computing, Mathematics and Statistics Group) ; no. 09/2003|
|Item Type: ||Monograph|
|Abstract: ||This paper discusses the problem of visualizing data where there are underlying constraints that must be preserved.
For example, we may know that the data is inherently positive. We show how the Modified Quadratic Shepard
method, which interpolates scattered data of any dimensionality, can be constrained to preserve positivity. We do this by forcing the quadratic basis functions to be positive. The method can be extended to handle other types of contraints, including lower bound of 0 and upper bound of 1, as occurs with fractional data. A further extension allows general range restrictions, creating an interpolant that lies between any two specified functions as the
lower and upper bounds.|
|Persistent URL (URI): ||http://hdl.handle.net/10182/1011|
|Appears in Collections:||Applied Computing Research Report series|
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