Lectures (Video)
- 1. Overview
- 2. Linear Functions
- 3. Linear algebra review
- 4. Orthonormal sets of vectors and QR factorization
- 5. Least-squares
- 6. Least-squares applications
- 7. Regularized least-squares and Gauss-Newton method
- 8. Least-norm solutions of underdetermined equations
- 9. Autonomous linear dynamical systems
- 10. High Order Linear Dynamical Systems
- 11. Solution via Laplace transform and matrix exponential
- 12. Eigenvectors and diagonalization
- 13. Jordan canonical form
- 14. Linear dynamical systems with inputs and outputs
- 15. Eigenvalues Of Symmetric Matrices
- 16. Symmetric matrices, quadratic forms, matrix norm, and SVD
- 17. SVD applications
- 18. Example: Quantum mechanics
- 19. Controllability and state transfer
- 20. Observability and state estimation
Introduction to Linear Dynamical Systems - Lecture 7
|
Get the Flash Player to view video.
Lecture 7 - Regularized least-squares and Gauss-Newton method
Least-Squares Polynomial Fitting, Norm Of Optimal Residual Versus P, Least-Squares System Identification, Model Order Selection, Cross-Validation, Recursive Least-Squares, Multi-Objective Least-Squares
Prof. Stephen P. Boyd
Introduction to Linear Dynamical Systems EE263 (Stanford University: Stanford Engineering Everywhere) http://see.stanford.edu Date accessed: 2009-09-25 License: Creative Commons Attribution 3.0 |
Lecture Material
To view the lecture material accompanying this lecture in a new window, please click the button below. If necessary, use the vertical or horizontal scrollbar in the new window to view more of the material or you can resize the window.
To download the above lecture material use this link. (Right-click and select Save Target As or Save Link As.)
