Quiver Signal Processing (QSP)

10/22/2020
by   Alejandro Parada-Mayorga, et al.
0

In this paper we state the basics for a signal processing framework on quiver representations. A quiver is a directed graph and a quiver representation is an assignment of vector spaces to the nodes of the graph and of linear maps between the vector spaces associated to the nodes. Leveraging the tools from representation theory, we propose a signal processing framework that allows us to handle heterogeneous multidimensional information in networks. We provide a set of examples where this framework provides a natural set of tools to understand apparently hidden structure in information. We remark that the proposed framework states the basis for building graph neural networks where information can be processed and handled in alternative ways.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/21/2020

Gasper: GrAph Signal ProcEssing in R

We present a short tutorial on to the use of the R gasper package. Gaspe...
research
06/09/2022

Abstract message passing and distributed graph signal processing

Graph signal processing is a framework to handle graph structured data. ...
research
02/24/2017

Unifying local and non-local signal processing with graph CNNs

This paper deals with the unification of local and non-local signal proc...
research
05/11/2023

Generalized signals on simplicial complexes

Topological signal processing (TSP) over simplicial complexes typically ...
research
12/31/2018

Theory and Algorithms for Pulse Signal Processing

The integrate and fire converter transforms an analog signal into train ...
research
04/17/2018

Sampling of graph signals via randomized local aggregations

Sampling of signals defined over the nodes of a graph is one of the cruc...
research
07/11/2020

A Tutorial on Graph Theory for Brain Signal Analysis

This tutorial paper refers to the use of graph-theoretic concepts for an...

Please sign up or login with your details

Forgot password? Click here to reset