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Demixing and blind deconvolution of graph-diffused signals

Citation Author(s):
Fernando J. Iglesias, Santiago Segarra, Samuel Rey-Escudero, Antonio G. Marques, David Ramirez
Submitted by:
Fernando Jose I...
Last updated:
19 April 2018 - 4:51pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters:
Santiago Segarra
Paper Code:
3185
 

We extend the classical joint problem of signal demixing, blind deconvolution,
and filter identification to the realm of graphs. The model is that
each mixing signal is generated by a sparse input diffused via a graph filter.
Then, the sum of diffused signals is observed. We identify and address
two problems: 1) each sparse input is diffused in a different graph; and 2)
all signals are diffused in the same graph. These tasks amount to finding
the collections of sources and filter coefficients producing the observation.

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