Beginning with excellent background material, this book
makes the study of random signal analysis manageable and easily
With comprehensive and detailed coverage
of Wiener filtering and Kalman filtering, this book presents a coherent
treatment of estimation theory and an in-depth look at detection (or
template matching) theory for communication and pattern recognition.
3. Random Variables.
4. Random Vectors.
5. Signal Analysis Techniques.
6. Stochastic Processes.
7. Least-Square Techniques.
8. Optimum Filtering.
9. Template Matching.
Appendix A: Table of Normal Curve Areas.
Appendix B: Gauss-Jordan Matrix Inversion.
Appendix C: Symbolic Differentiation.