Blind identification of graph filters with multiple sparse inputs

  title={Blind identification of graph filters with multiple sparse inputs},
  author={Santiago Segarra and Antonio G. Marques and Gonzalo Mateos and Alejandro R. Ribeiro},
  journal={2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
Network processes are often represented as signals defined on the vertices of a graph. To untangle the latent structure of such signals, one can view them as outputs of linear graph filters modeling underlying network dynamics. This paper deals with the problem of joint identification of a graph filter and its input signal, thus broadening the scope of classical blind deconvolution of temporal and spatial signals to the less-structured graph domain. Given a graph signal y modeled as the output… CONTINUE READING
5 Citations
24 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 24 references

Distributed optimization and statistical learning via the alternating direction method of multipliers

  • S. Boyd, N. Parikh, E. Chu, B.Peleato, J. Eckstein
  • Found. Trends Machine Learn., vol. 3, pp. 1–122…
  • 2011
Highly Influential
2 Excerpts

Similar Papers

Loading similar papers…