Instructor: Prof. S. Mukhopadhyay, Department of Electrical Engineering, IIT Kharagpur.
This course covers lessons on probability theory, random variables, mean and variance, linear signal models, z-transform, Kalman filter, variants of least squares estimation, and estimation problems in instrumentation and control.
Overview
Syllabus
Lec-1 Introduction.
Lec-2 Probability Theory.
Lec-3 Random Variables.
Lec-4 Function of Random Variable Joint Density.
Lec-5 Mean and Variance.
Lec-6 Random Vectors Random Processes.
Lec-7 Random Processes and Linear Systems.
Lec-8 Some Numerical Problems.
Lec-9 Miscellaneous Topics on Random Process.
Lec-10 Linear Signal Models.
Lec-11 Linear Mean Sq.Error Estimation.
Lec-12 Auto Correlation and Power Spectrum Estimation.
lec-13 Z-Transform Revisited Eigen Vectors/Values.
Lec-14 The Concept of Innovation.
Lec-15 Last Squares Estimation Optimal IIR Filters.
Lec-16 Introduction to Adaptive FIlters.
Lec-17 State Estimation.
Lec-18 Kalman Filter-Model and Derivation.
Lec-19 Kalman Filter-Derivation(Contd...).
Lec-20 Estimator Properties.
Lec-21 The Time-Invariant Kalman Filter.
Lec-22 Kalman Filter-Case Study.
Lec-23 System identification Introductory Concepts.
Lec-24 Linear Regression-Recursive Least Squares.
Lec-25 Variants of LSE.
Lec-26 Least Square Estimation.
Lec-27 Model Order Selection Residual Tests.
Lec-28 Practical Issues in Identification.
Lec-29 Estimation Problems in Instrumentation and Control.
Lec-30 Conclusion.
Taught by
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