Introduction to Linear Dynamical Systems
1:16:46Introduction to Linear Dynamical Systems
1:05:52Introduction to Linear Dynamical Systems
1:19:10Introduction to Linear Dynamical Systems
1:14:08Introduction to Linear Dynamical Systems
1:15:14Introduction to Linear Dynamical Systems
1:16:19Introduction to Linear Dynamical Systems
1:15:46Least-Norm Solutions of Underdetermined Equations
1:15:58Autonomous Linear Dynamical Systems
1:09:02Autonomous Linear Dynamical Systems in Electrical Engineering
1:11:42Solutions via Laplace Transform and Matrix Exponentials
1:08:55Matrix Exponentials, Eigenvectors, and Diagonalization in LDS
1:13:37Generalized Eigenvectors, Diagonalization, and Jordan Canonical Form
1:13:02Applications of Jordan Canonical Form in LDS and Electrical Engineering
1:17:43Inputs, Outputs, and Symmetric Matrices in Linear Dynamical Systems
1:09:01Symmetric Matrices, Quadratic Forms, Matrix Norm, and SVDs in LDS
1:12:35Applications of Singular Value Decomposition in LDS and Electrical Engineering
1:16:52Applications of SVD, Controllability, and State Transfer in Electrical Engineering
1:15:14Controllability and State Transfer in Modern Electrical Engineering
1:10:30Observability and State Estimation
1:09:25Inputs, Outputs, and Symmetric Matrices in Linear Dynamical Systems
The session covers the fundamental concepts of inputs and outputs in linear dynamical systems, alongside an in-depth discussion of symmetric matrices and their properties. It emphasizes their role in system behavior.
Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on inputs and outputs of linear dynamical systems, as well as symmetric matrices for the course, Introduction to Linear Dynamical Systems (EE263).
Introduction to applied linear algebra and linear dynamical systems, with applications to circuits, signal processing, communications, and control systems. Topics include: Least-squares aproximations of over-determined equations and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm and singular value decomposition. Eigenvalues, left and right eigenvectors, and dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input multi-output systems, impulse and step matrices; convolution.
Applications of Jordan Canonical Form in LDS and Electrical Engineering
Next · Lecture 16Symmetric Matrices, Quadratic Forms, Matrix Norm, and SVDs in LDS