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

1:16:46
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Introduction to Linear Dynamical Systems

1:05:52
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Introduction to Linear Dynamical Systems

1:19:10
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Introduction to Linear Dynamical Systems

1:14:08
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Introduction to Linear Dynamical Systems

1:15:14
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Introduction to Linear Dynamical Systems

1:16:19
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Introduction to Linear Dynamical Systems

1:15:46
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Least-Norm Solutions of Underdetermined Equations

1:15:58
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Autonomous Linear Dynamical Systems

1:09:02
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Autonomous Linear Dynamical Systems in Electrical Engineering

1:11:42
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Solutions via Laplace Transform and Matrix Exponentials

1:08:55
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Matrix Exponentials, Eigenvectors, and Diagonalization in LDS

1:13:37
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Generalized Eigenvectors, Diagonalization, and Jordan Canonical Form

1:13:02
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Applications of Jordan Canonical Form in LDS and Electrical Engineering

1:17:43
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Inputs, Outputs, and Symmetric Matrices in Linear Dynamical Systems

1:09:01
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Symmetric Matrices, Quadratic Forms, Matrix Norm, and SVDs in LDS

1:12:35
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Applications of Singular Value Decomposition in LDS and Electrical Engineering

1:16:52
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Applications of SVD, Controllability, and State Transfer in Electrical Engineering

1:15:14
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Controllability and State Transfer in Modern Electrical Engineering

1:10:30
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Observability and State Estimation

1:09:25

Applications of Singular Value Decomposition in LDS and Electrical Engineering

Stephen BoydDistinguishedStanford University

Professor

1:16:52·2008·graduate level

This lecture explores the diverse applications of Singular Value Decomposition (SVD) within linear dynamical systems and various electrical engineering problems. It showcases SVD's utility in data analysis and system reduction.

MathematicsEngineeringLinear AlgebraSignal Processing & RoboticsControl & Dynamical SystemsSingular Value Decomposition

Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on the applications of single value decomposition in LDS and electrical engineering, Introduction to Linear Dynamical Systems (EE263).

Source: Stanford via YouTubeWatch on YouTube
LecturerAll lecturers →
Stephen BoydDistinguished

Samsung Professor of Engineering, Stanford & Co-Author of Convex Optimization

Samsung Professor of Engineering at Stanford whose textbook and EE364a lectures established convex optimization as a core language across control, signal processing, and ML.

2 courses · 43 lecturesCanon
Previous · Lecture 16

Symmetric Matrices, Quadratic Forms, Matrix Norm, and SVDs in LDS

Next · Lecture 18

Applications of SVD, Controllability, and State Transfer in Electrical Engineering

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