Independent component analysis: theory and applications

摘要: Abstract. Preface. Acknowledgments. List of Figures. Tables. Abbreviations and Symbols. Introduction. Part I: Independent Component Analysis: Theory. 1. Basics. 2. Analysis. 3. A Unifying Information-Theoretic Framework for ICA. 4. Blind Separation Time-Delayed Convolved Sources. 5. ICA Using Overcomplete Representations. 6. First Steps towards Nonlinear II: Applications. 7. Biomedical Applications 8. Feature Extraction. 9. Unsupervised Classification with Mixture Models. 10. Conclusions Future Research. Bibliography. About the Author. Index.