Independent Component Analysis: Theory and Applications

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