| Lec # | Topics |
|---|---|
|
1 |
Introduction Content of the Course |
|
2 |
Examples of Inverse Problems, Static and Time Dependent |
|
3 |
Basic Vector/Matrix Notation Algebraic Formulation |
|
4-6 |
Over/Underdetermined Problems Varieties of Least-Squares |
|
7 |
Basic Statistics Concepts and Notation |
|
8 |
Variances/Covariances Biases of Solutions |
|
9 |
Special Case of Eigenvector Solutions |
|
10-11 |
Singular Value Decomposition and Singular Vector Solutions |
|
12-13 |
Recursive Least-Squares Gauss-Markov Estimation; Recursive Estimation |
|
14 |
Time-dependent Models Whole Domain Least-Squares |
|
15-16 |
Sequential Methods (Kalman Filter/RTS Smoother) |
|
16-17 |
Control Problems Lagrange Multiplier (adjoint) Methods Non-linear Problems |
|
18 |
Stationary Processes Numerical Fourier Series/Transforms; Delta Functions |
|
19 |
Statistics of Fourier Representations Sampling Periodograms |
|
20 |
Convolution Power Density Spectral Estimates |
|
21 |
Coherence; Multiple Linear Regression |
|
22 |
Filtering, Prediction Problems |
|
23-24 |
Special Topics, Spillover |
Calendar
Course Info
Instructor
Departments
As Taught In
Spring
2005
Level
Course Info
Instructor
Departments
As Taught In
Spring
2005
Level
Learning Resource Types
notes
Lecture Notes
assignment
Problem Sets
assignment
Programming Assignments