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Lecture
Primitive Matrices and Spectral Properties in Networked Control Systems
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Related lectures (28)
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Characteristic Polynomials and Similar Matrices
Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.
Spectral Theorem Recap
Revisits the spectral theorem for symmetric matrices, emphasizing orthogonally diagonalizable properties and its equivalence with symmetric bilinear forms.
Diagonalization of Symmetric Matrices
Explores the diagonalization of symmetric matrices through orthogonal decomposition and the spectral theorem.
Diagonalization of Symmetric Matrices
Covers the diagonalization of symmetric matrices, the spectral theorem, and the use of spectral decomposition.
Eigenvalues and Fibonacci Sequence
Covers eigenvalues, eigenvectors, and the Fibonacci sequence, exploring their mathematical properties and practical applications.
Matrix Computations: Eigenvalues and Eigenvectors
Explores the complexity of matrix computations, focusing on eigenvalues and eigenvectors of symmetric matrices and the challenges in computing them.
Eigenvalues and Eigenvectors of Markov Chains
Explores eigenvalues and eigenvectors of Markov chains, focusing on convergence rates and matrix properties.
Matrices and Quadratic Forms: Key Concepts in Linear Algebra
Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.
Matrices and Networks
Explores the application of matrices and eigendecompositions in networks.
Networked Control Systems: Consensus and Connectivity
Explores consensus algorithms and connectivity properties in networked control systems.
