Projects per year
Abstract
The first step in any graph signal processing (GSP) task is to learn the graph signal representation, i.e., to capture the dependence structure of the data into an adjacency matrix. Indeed, the adjacency matrix is typically not known a priori and has to be learned. However, it is learned with errors. A little, if any, attention has been paid to modeling such errors in the adjacency matrix, and studying their effects on GSP tasks. Modeling errors in adjacency matrix will enable both to study the graph error effects in GSP and to develop robust GSP algorithms. In this paper, we therefore introduce practically justifiable graph error models. We also study, both analytically and in terms of simulations, the graph error effect on the performance of GSP based on the example of independent component analysis of graph signals (graph decorrelation).
Original language  English 

Title of host publication  2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) 
Publisher  IEEE 
Pages  41644168 
Number of pages  5 
ISBN (Electronic)  9781538646588 
DOIs  
Publication status  Published  2018 
MoE publication type  A4 Article in a conference publication 
Event  IEEE International Conference on Acoustics, Speech, and Signal Processing  Calgary, Canada Duration: 15 Apr 2018 → 20 Apr 2018 https://2018.ieeeicassp.org/ 
Publication series
Name  Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing 

ISSN (Electronic)  2379190X 
Conference
Conference  IEEE International Conference on Acoustics, Speech, and Signal Processing 

Abbreviated title  ICASSP 
Country  Canada 
City  Calgary 
Period  15/04/2018 → 20/04/2018 
Internet address 
Keywords
 ErdosRenyi graphs
 error effect
 graph signal processing
 minimum distance index
 shift matrix
 NETWORKS
Projects
 2 Finished

Robust Statistics for Highdimensional Data
Ollila, E., Raninen, E., Basiri, S. & Tabassum, M. N.
01/09/2016 → 31/12/2020
Project: Academy of Finland: Other research funding

Transmit beamspace for active compressive sensing and communication with multiple waveforms
Kocharlakota, K., Upadhya, K., Rizwan Ullah, R., Gao, R., Vorobyov, S., Ghorbani Veshki, F. & Dosti, E.
01/09/2016 → 31/08/2020
Project: Academy of Finland: Other research funding