cupyx.scipy.signal.gauss_spline#

cupyx.scipy.signal.gauss_spline(x, n)[source]#

Gaussian approximation to B-spline basis function of order n.

Parameters:

  • x (array_like) – a knot vector

  • n (int) – The order of the spline. Must be nonnegative, i.e. n >= 0

Returns:

res – B-spline basis function values approximated by a zero-mean Gaussian function.

Return type:

ndarray

Notes

The B-spline basis function can be approximated well by a zero-mean Gaussian function with standard-deviation equal to \(\sigma=(n+1)/12\) for large n :

\[\frac{1}{\sqrt {2\pi\sigma^2}}exp(-\frac{x^2}{2\sigma})\]

See [1], [2] for more information.

References