Non-parametric approach to ICA using kernel density estimation

@inproceedings{Sengupta2003NonparametricAT,
  title={Non-parametric approach to ICA using kernel density estimation},
  author={Kuntal Sengupta and Prabir Burman},
  booktitle={ICME},
  year={2003}
}
Independent Component Analysis (ICA) has found a wide range of applications in signal processing and multimedia, ranging from speech cleaning to face recognition. This paper presents a non-parametric approach to the ICA problem that is robust towards outlier effects. The algorithm, for the first time in the field of ICA, adopts an intuitive and direct approach, focusing on the very definition of independence itself; i.e. the joint probability density function (pdf) of independent sources is… CONTINUE READING

Citations

Publications citing this paper.

Independent Component Analysis based on Nonparametric Density Estimation on Time-Frequency Domain

2005 IEEE Workshop on Machine Learning for Signal Processing • 2005
View 4 Excerpts
Highly Influenced

References

Publications referenced by this paper.
Showing 1-10 of 11 references

Similar Papers

Loading similar papers…