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Nonlinear blind source separation using kernel feature spaces

2001

Conference Paper

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In this work we propose a kernel-based blind source separation (BSS) algorithm that can perform nonlinear BSS for general invertible nonlinearities. For our kTDSEP algorithm we have to go through four steps: (i) adapting to the intrinsic dimension of the data mapped to feature space F, (ii) finding an orthonormal basis of this submanifold, (iii) mapping the data into the subspace of F spanned by this orthonormal basis, and (iv) applying temporal decorrelation BSS (TDSEP) to the mapped data. After demixing we get a number of irrelevant components and the original sources. To find out which ones are the components of interest, we propose a criterion that allows to identify the original sources. The excellent performance of kTDSEP is demonstrated in experiments on nonlinearly mixed speech data.

Author(s): Harmeling, S. and Ziehe, A. and Kawanabe, M. and Blankertz, B. and Müller, K-R.
Book Title: ICA 2001
Journal: Proceedings of the Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001)
Pages: 102-107
Year: 2001
Month: December
Day: 0
Editors: Lee, T.-W. , T.P. Jung, S. Makeig, T. J. Sejnowski

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: Third International Workshop on Independent Component Analysis and Blind Signal Separation
Event Place: San Diego, CA, USA

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF

BibTex

@inproceedings{6364,
  title = {Nonlinear blind source separation using kernel feature spaces},
  author = {Harmeling, S. and Ziehe, A. and Kawanabe, M. and Blankertz, B. and M{\"u}ller, K-R.},
  journal = {Proceedings of the Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001)},
  booktitle = {ICA 2001},
  pages = {102-107},
  editors = {Lee, T.-W. , T.P. Jung, S. Makeig, T. J. Sejnowski},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = dec,
  year = {2001},
  month_numeric = {12}
}