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Minimum Sobolev Norm Interpolation
PDE & Applied Mathematics| Speaker: | Shiv Chandrasekaran, UC Santa Barbara |
| Location: | 2112 MSB |
| Start time: | Thu, Feb 28 2008, 2:10PM |
Description
It is well-known that classical polynomial interpolation
with an N-th degree polynomial at N+1 equally spaced sample points can
diverge even when the underlying function is analytic in a region
containing the samples. This is known as the Runge phenomenon. In this
talk we will present a family of schemes to construct interpolating
polynomials that will converge no matter where the samples lie (the
underlying function must satisfy a very mild smoothness condition;
first derivative is not required for example). The convergence is, of
course, only at limit points of the samples. The technique we present
generalizes to any set of basis functions (not just polynomials) for
which suitable Sobolev norms can be defined (for example,
Laplace-Beltrami eigenfunctions on manifolds). Since our method places
no constraints on the sample points, we can easily handle difficult
approximation problems in high-dimensional spaces where the samples
are restricted to complicated regions. Furthermore, our method
exhibits "rapid local convergence" properties. By this we mean, that
our interpolating polynomials will converge rapidly where the function
is smooth, and more slowly where the function is singular. Note that
such properties are more traditionally associated with wavelets. If
time permits, we will show how these schemes can be used to construct
meshless discretizations of differential and integral equations.
This is joint work with M. Gu, H. Mhaskar, K. Raghuram, N. Somasundaram.
Note special time and room. There are two of the seminar series on this day.
