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