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Stanford EE263: Introduction to Linear Dynamical Systems →0/20
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Lecture 1 | Introduction to Linear Dynamical Systems

1:16:46
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Lecture 2 | Introduction to Linear Dynamical Systems

1:05:52
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Lecture 3 | Introduction to Linear Dynamical Systems

1:19:10
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Lecture 4 | Introduction to Linear Dynamical Systems

1:14:08
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Lecture 5 | Introduction to Linear Dynamical Systems

1:15:14
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Lecture 6 | Introduction to Linear Dynamical Systems

1:16:19
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Lecture 7 | Introduction to Linear Dynamical Systems

1:15:46
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Lecture 8: Least-Norm Solutions of Underdetermined Equations (EE263)

1:15:58
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Lecture 9: Autonomous Linear Dynamical Systems (EE263)

1:09:02
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Lecture 10: Autonomous Linear Dynamical Systems in Electrical Engineering (EE263)

1:11:42
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Lecture 11: Solutions via Laplace Transform and Matrix Exponentials (EE263)

1:08:55
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Lecture 12: Matrix Exponentials, Eigenvectors, and Diagonalization in LDS (EE263)

1:13:37
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Lecture 13: Generalized Eigenvectors, Diagonalization, and Jordan Canonical Form (EE263)

1:13:02
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Lecture 14: Applications of Jordan Canonical Form in LDS and Electrical Engineering (EE263)

1:17:43
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Lecture 15: Inputs, Outputs, and Symmetric Matrices in Linear Dynamical Systems (EE263)

1:09:01
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Lecture 16: Symmetric Matrices, Quadratic Forms, Matrix Norm, and SVDs in LDS (EE263)

1:12:35
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Lecture 17: Applications of Singular Value Decomposition in LDS and Electrical Engineering (EE263)

1:16:52
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Lecture 18: Applications of SVD, Controllability, and State Transfer in Electrical Engineering (EE263)

1:15:14
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Lecture 19: Controllability and State Transfer in Modern Electrical Engineering (EE263)

1:10:30
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Lecture 20: Observability and State Estimation (EE263)

1:09:25

Lecture 2 | Introduction to Linear Dynamical Systems

Stephen BoydStanford University

Samsung Professor in the School of Engineering

1:05:52·2008·graduate level

Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on linear functions for the course, Introduction to Linear Dynamical Systems (EE263).

MathematicsEngineeringLinear AlgebraControl & Dynamical SystemsSignal Processing & Roboticsscience

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 and transfer matrix descriptions.

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Lecture 1 | Introduction to Linear Dynamical Systems

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