Polynomial and spline approximation by quadratic programming
By D. E. Amos, M. L. Slater
Communications of the ACM,
Vol. 12 No. 7, Pages 379-380
10.1145/363156.363163
The problem of approximation to a given function, or of fitting a given set of data, where the approximating function is required to have certain of its derivatives of specified sign over the whole range of approximation, is studied. Two approaches are presented, in each of which quadratic programming is used to provide both the constraints on the derivatives and the selection of the function which yields the best fit. The first is a modified Berstein polynomial scheme, and the second is a spline fit.
The full text of this article is premium content
0 Comments
No entries found
Log in to Read the Full Article
Purchase the Article
Log in
Create a Web Account
If you are an ACM member, Communications subscriber, Digital Library subscriber, or use your institution's subscription, please set up a web account to access premium content and site
features. If you are a SIG member or member of the general public, you may set up a web account to comment on free articles and sign up for email alerts.