Analyzing the Approximation Error of the Fast Graph Fourier Transform
Numerical Analysis
2017-11-07 v2
Abstract
The graph Fourier transform (GFT) is in general dense and requires O(n^2) time to compute and O(n^2) memory space to store. In this paper, we pursue our previous work on the approximate fast graph Fourier transform (FGFT). The FGFT is computed via a truncated Jacobi algorithm, and is defined as the product of J Givens rotations (very sparse orthogonal matrices). The truncation parameter, J, represents a trade-off between precision of the transform and time of computation (and storage space). We explore further this trade-off and study, on different types of graphs, how is the approximation error distributed along the spectrum.
Cite
@article{arxiv.1711.00386,
title = {Analyzing the Approximation Error of the Fast Graph Fourier Transform},
author = {Luc LeMagoarou and Nicolas Tremblay and Rémi Gribonval},
journal= {arXiv preprint arXiv:1711.00386},
year = {2017}
}
Comments
ASILOMAR conference