Multivariate and Rational Splines
with Bu,k,Bv,l,Bw,m univariate B-splines. Correspondingly, this spline is of order k in x, of order l in y, and of order m in z. Similarly, the ppform of a tensor-product spline is specified by break sequences in each of the variables and, for each hyper-rectangle thereby specified, a coefficient array. Further, as in the univariate case, the coefficients may be vectors, typically 2-vectors or 3-vectors, making it possible to represent, e.g., certain surfaces in ℜ3.
with ψ(x)=|x|2log|x|2 the thin-plate spline basis function, and |x| denoting the Euclidean length of the vector x. Here, for convenience, denote the independent variable by x, but x is now a vector whose two components, x(1) and x(2), play the role of the two independent variables earlier denoted x and y. Correspondingly, the sites cj are points in ℜ2.
over all sufficiently smooth functions f. Here, the yi are data values given at the data sites ci, p is the smoothing parameter, and Djf denotes the partial derivative of f with respect to x(j). The integral is taken over the entire ℜ2. The upper summation limit, n–3, reflects the fact that 3 degrees of freedom of the thin-plate spline are associated with its polynomial part.
Thin-plate splines are functions in stform, meaning that, up to certain polynomial terms, they are a weighted sum of arbitrary or scattered translates Ψ(· -c) of one fixed function, Ψ. This so-called basis function for the thin-plate spline is special in that it is radially symmetric, meaning that Ψ(x) only depends on the Euclidean length, |x|, of x. For that reason, thin-plate splines are also known as RBFs or radial basis functions. See Constructing and Working with stform Splines for more information.
A rational spline is any function of the form r(x) = s(x)/w(x), with both s and w splines and, in particular, w a scalar-valued spline, while s often is vector-valued.
Rational splines are attractive because it is possible to describe various basic geometric shapes, like conic sections, exactly as the range of a rational spline. For example, a circle can so be described by a quadratic rational spline with just two pieces.
In this toolbox, there is the additional requirement that both s and w be of the same form and even of the same order, and with the same knot or break sequence. This makes it possible to store the rational spline r as the ordinary spline R whose value at x is the vector [s(x);w(x)]. Depending on whether the two splines are in B-form or ppform, such a representation is called here the rBform or the rpform of such a rational spline.
It is easy to obtain r from R. For example, if
v is the value of R at x,
v(1:end-1)/v(end) is the value of r at
x. As another example, consider getting derivatives of r from those of R.
Because s = wr, Leibniz' rule tells us that
where Dms the mth derivative of s.
j = 1...
m + 1, then
provides the value of DmR(x).