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box spline : ウィキペディア英語版
box spline
In the mathematical fields of numerical analysis and approximation theory, box splines are piecewise polynomial functions of several variables. Box splines are considered as a multivariate generalization of basis splines (B-splines) and are generally used for multivariate approximation/interpolation. Geometrically, a box spline is the shadow (X-ray) of a hypercube projected down to a lower-dimensional space. Box splines and simplex splines are well studied special cases of polyhedral splines which are defined as shadows of general polytopes.
==Definition==
A box spline is a multivariate function (\mathbb^d \to \mathbb ) defined for a set of vectors, \xi \in \mathbb^d, usually gathered in a matrix \mathbf := \left(\dots \xi_N\right ) .
When the number of vectors is the same as the dimension of the domain (i.e., N = d ) then the box spline is simply the (normalized) indicator function of the parallelepiped formed by the vectors in \mathbf:
: M_) := \frac\chi_) = \begin \frac & \mathbf = \sum_^d \text 0 \le t_n < 1 \\ 0 & \text\end.
Adding a new direction, \xi, to \mathbf, or generally when N > d, the box spline is defined recursively:〔
: M_(\mathbf) = \int_0^1- t \xi) \, t}.
The box spline M_^N when projected down into \mathbb^d. In this view, the vectors \xi \in \mathbf are the geometric projection of the standard basis in \mathbb^N (i.e., the edges of the hypercube) to \mathbb^d.
Considering tempered distributions a box spline associated with a single direction vector is a Dirac-like generalized function supported on t\xi for 0 \le t < 1. Then the general box spline is defined as the convolution of distributions associated the single-vector box splines:
:M_ \ast M_ \dots \ast M_.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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