more background info

Author: stevengj

README.md

@@ -2,9 +2,11 @@
 
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-Fast multidimensional Chebyshev interpolation on a hypercube (Cartesian-product)
+Fast multidimensional Chebyshev polynomial interpolation on a hypercube (Cartesian-product)
 domain, using a separable (tensor-product) grid of Chebyshev interpolation points, as well as Chebyshev regression (least-square fits) from an arbitrary set of points.   In both cases we support arbitrary dimensionality, complex and vector-valued functions, and fast derivative and Jacobian computation.
 
+[Chebyshev polynomials](https://en.wikipedia.org/wiki/Chebyshev_polynomials) are simply a well-behaved basis for polynomial functions in a given finite interval, so you can view FastChebInterp as a robust and convenient way to do perform multidimensional polynomial fitting and interpolation.   Fitting to high-degree polynomials can be problematic unless your number of data points is much greater than the product of the polynomial degrees (the number of polynomial terms), but if you have a [smooth function](https://en.wikipedia.org/wiki/Smoothness) and interpolate from specially chosen points — the Chebyshev points, given by the function `chebpoints` below — then it is very well behaved, and in fact converges exponentially fast for analytic functions.  (See, for example, the book [*Approximation Theory and Approximation Practice*](https://www.chebfun.org/ATAP/) by Trefethen.)
+
 ## Usage
 
 For domain upper and lower bounds `lb` and `ub`, and a given `order`