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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 9: Autonomous Linear Dynamical Systems (EE263)

Stephen BoydStanford University

Professor

1:09:02·2008·graduate level

The session focuses on the theoretical underpinnings and practical implications of autonomous linear dynamical systems. It covers the fundamental principles governing system evolution without external inputs.

MathematicsEngineeringSignal Processing & RoboticsLinear AlgebraControl & Dynamical SystemsAutonomous Systems

Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on autonomous linear dynamical systems 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 approximations 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.

Previous · Lecture 8

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

Next · Lecture 10

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

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