1-Introduction
2-Detection and classification
3-Parameter estimation
4-State estimation
5-Supervised learning
6-Feature extraction and selection
7-Unsupervised learning
8-State estimation in practice
9-Worked out examples
Appendix A:Topics selected from functional analysis
Appendix B:Topics selected from linear algebra and matrix theory
Appendix C:Probability theory
Appendix D:Discrete-time dynamic systems
Appendix E:Introduction to PRTools
Appendix F:MATLAB toolbox used
