A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation

Mathematics – Numerical Analysis

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

For high dimensional problems, such as approximation and integration, one cannot afford to sample on a grid because of the curse of dimensionality. An attractive alternative is to sample on a low discrepancy set, such as an integration lattice or a digital net. This article introduces a multivariate fast discrete Walsh transform for data sampled on a digital net that requires only $O(N \log N)$ operations, where $N$ is the number of data points. This algorithm and its inverse are digital analogs of multivariate fast Fourier transforms. This fast discrete Walsh transform and its inverse may be used to approximate the Walsh coefficients of a function and then construct a spline interpolant of the function. This interpolant may then be used to estimate the function's effective dimension, an important concept in the theory of numerical multivariate integration. Numerical results for various functions are presented.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Multivariate Fast Discrete Walsh Transform with an Application to Function Interpolation will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-385118

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.