Estimation of Signals and Systems

Estimation of Signals and Systems
Lecture Series on Estimation of Signals and Systems by Prof.S. Mukhopadhyay, Department of Electrical Engineering, IIT Kharagpur.
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