eigendec

Eigen decomposition of dense symmetric/hermitian matrix M
using divide-and-conquer methods that provides slightly different results
than the standard method, but is considerably faster for large matrices.

Provides the standard operations for signal processing on graphs:
graph Fourier transform, spectral graph wavelet transform,
visualization tools. It also implements a data driven method
for graph signal denoising/regression, for details see
De Loynes, Navarro, Olivier (2019) <arxiv:1906.01882>.
The package also provides an interface to the SuiteSparse Matrix Collection,
<https://sparse.tamu.edu/>, a large and widely used set of sparse matrix
benchmarks collected from a wide range of applications.

Fabien Navarro

gasper

Graph Signal Processing

Basile de Loynes

Baptiste Olivier

eigendec function

<dl><dt>M</dt>
<dd>a matrix.</dd></dl>

Arguments

Spectral decomposition of a symetric matrix — eigendec

<dl>

<dt>M</dt>
<dd>a matrix.</dd>

</dl>

eigendec: Spectral decomposition of a symetric matrix

Description

Usage

Arguments