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Transcript
Abstract:
The main problem of approximation theory is to resolve a complicated target function by a sequence
of functions of small complexity. In linear approximation, the approximating functions are chosen
from pre-specified finite-dimensional vector spaces. However, in many problems one can gain
considerably by allowing the approximation method to "adapt" to the target function. The
approximants will then typically belong to nonlinear manifolds rather than linear spaces, hence the
name nonlinear methods of approximation. Nowadays, such methods are used throughout
mathematics and science.
My goal is to present some basic facts from nonlinear approximation theory in an informal way. In
particular, function spaces will be kept to an appropriate minimum.
If time permits, I will discuss recent joint work with P. Petrushev (USC) on highly nonlinear spline
approximation.