A Minimum-Range Approach to Blind Extraction of Bounded Sources

@article{Vrins2007AMA,
  title={A Minimum-Range Approach to Blind Extraction of Bounded Sources},
  author={Fr{\'e}d{\'e}ric Vrins and John Aldo Lee and Michel Verleysen},
  journal={IEEE Transactions on Neural Networks},
  year={2007},
  volume={18},
  pages={809-822}
}
In spite of the numerous approaches that have been derived for solving the independent component analysis (ICA) problem, it is still interesting to develop new methods when, among other reasons, specific a priori knowledge may help to further improve the separation performances. In this paper, the minimum-range approach to blind extraction of bounded source is investigated. The relationship with other existing well-known criteria is established. It is proved that the minimum-range approach is a… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 39 REFERENCES

SWM : a class of convex contrasts for source separation

  • Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.
  • 2005
VIEW 4 EXCERPTS

The minimum support criterion for blind source extraction: a limiting case of the strengthened Young’s inequality

S. Cruces, I. Duran
  • Lecture Notes in Computer Science, ser. LNCS 3195, C. Puntonet and A. Prieto, Eds. Berlin, Germany: Springer-Verlag, Sep. 2004, pp. 57–64.
  • 2004
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Blind separation of instantaneous mixture of sources based on order statistics

  • IEEE Trans. Signal Processing
  • 2000
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

A Least Absolute Bound Approach to ICA - Application to the MLSP 2006 Competition

  • 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing
  • 2006
VIEW 1 EXCERPT