Estimation of Signals and Systems

Indian Institute of Technology Kharagpur

This course covers lessons on probability theory, random variables, mean and variance, linear signal models, Z-transform, kalman filter, variants of LSE and estimation problems in instrumentation and control.

  1. Introduction
  2. Probability Theory
  3. Random Variables
  4. Function of Random Variable Joint Density
  5. Mean and Variance
  6. Random Vectors Random Processes
  7. Random Processes and Linear Systems
  8. Some Numerical Problems
  9. Miscellaneous Topics on Random Process
  10. Linear Signal Models
  11. Linear Mean Sq.Error Estimation
  12. Auto Correlation and Power Spectrum Estimation
  13. Z-Transform Revisited Eigen Vectors/Values
  14. The Concept of Innovation
  15. Last Squares Estimation Optimal IIR Filters
  16. Introduction to Adaptive Filters
  17. State Estimation
  18. Kalman Filter-Model and Derivation
  19. Kalman Filter-Derivation (Contd...)
  20. Estimator Properties
  21. The Time-Invariant Kalman Filter
  22. Kalman Filter-Case Study
  23. System identification Introductory Concepts
  24. Linear Regression-Recursive Least Squares
  25. Variants of LSE
  26. Least Square Estimation
  27. Model Order Selection Residual Tests
  28. Practical Issues in Identification
  29. Estimation Problems in Instrumentation and Control
  30. Conclusion
Course Lectures