A general solution to blind inverse problems for sparse input signals

@article{Luengo2005AGS,
  title={A general solution to blind inverse problems for sparse input signals},
  author={David Luengo and Ignacio Santamar{\'i}a and Luis Vielva},
  journal={Neurocomputing},
  year={2005},
  volume={69},
  pages={198-215}
}
ification; In this paper, we present a computationally efficient algorithm which provides a solution to blind inverse problems for sparse input signals. The method takes advantag clustering typical of sparse input signals to identify the channel matrix, solving four p sequentially: detecting the number of input signals (i.e. clusters), estimating the direc the clusters, estimating their amplitudes, and ordering them. Once the channel m known, the pseudoinverse can be used as the canonical… CONTINUE READING

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