pittsburgh

A dataset containing the pittsubrgh network.

datasets

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

pittsburgh function

list of 7 elements<dl>
<dt>A</dt>
<dd>pittsburgh adjacency matrix</dd><dt>sA</dt>
<dd>pittsburgh sparse adjacency matrix</dd><dt>xy</dt>
<dd>coordinates</dd><dt>f</dt>
<dd>signal used in Trend filtering on graphs</dd><dt>y</dt>
<dd>noisy signal used in Trend filtering on graph</dd><dt>f1</dt>
<dd>eta=0.01, k=5</dd><dt>geo</dt>
<dd>geometry</dd>
</dl>

Format

Pittsburgh network. — pittsburgh

list of 7 elements<dl>
<dt>A</dt>
<dd>pittsburgh adjacency matrix</dd>

<dt>sA</dt>
<dd>pittsburgh sparse adjacency matrix</dd>

<dt>xy</dt>
<dd>coordinates</dd>

<dt>f</dt>
<dd>signal used in Trend filtering on graphs</dd>

<dt>y</dt>
<dd>noisy signal used in Trend filtering on graph</dd>

<dt>f1</dt>
<dd>eta=0.01, k=5</dd>

<dt>geo</dt>
<dd>geometry</dd>


</dl>

pittsburgh: Pittsburgh network.

Description

Usage

Arguments

Format