Estimation of Signals and Systems

Estimation of Signals and Systems

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Lec-14 The Concept of Innovation

14 of 30

14 of 30

Lec-14 The Concept of Innovation

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Classroom Contents

Estimation of Signals and Systems

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

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