public class RadialBasisEx1 extends Object
RadialBasis Example 1: Approximates a function with a Hardy multiquadric radial basis function.
Data is generated from the function $$e^{-\|\vec{x}\|^2/d}$$ where d is the dimension, is evaluated at a set of randomly chosen points. Random noise is added to the values and a radial basis approximation to the noisy data is computed. The radial basis fit, using the default radial basis function Hardy multiquadric with \(\delta=1\), is then compared to the original function at another set of randomly chosen points. Both the average error and the maximum error are computed and printed.In this example, the dimension d=10. The function is sampled at 200 random points, in the \([-1,1]^d\) hyper-cube, to which what noise in the range [-0.2,0.2] is added. The error is computed at 1000 random points, also from the \([-1,1]^d\) hyper-cube. The compute errors are less than the added noise.
Constructor and Description |
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RadialBasisEx1() |
public static void main(String[] args)
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