We address the problem of computing a good floating-point-coefficient polynomial approximation to a function, with respect to the supremum norm. This is a key step in most processes of evaluation of a function. We present a fast and efficient method, based on lattice basis reduction, that often gives the best polynomial possible and most of the time returns a very good approximation.
Index Terms:
Efficient polynomial approximation, floating-point arithmetic, absolute error, L norm, lattice basis reduction, closest vector problem, LLL algorithm.
Citation:
Nicolas Brisebarre, Sylvain Chevillard, "Efficient polynomial L-approximations," arith, pp.169-176, 18th IEEE Symposium on Computer Arithmetic (ARITH '07), 2007