Главная
Study mode:
on
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
Description:
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.

Estimation of Signals and Systems

NPTEL
Add to list
#Engineering #Electrical Engineering #Telecommunications #Signal Processing #Kalman Filter #Mathematics #Statistics & Probability #Probability Theory
0:00 / 0:00
1 of 30

Lec-1 Introduction