Lectures related to Networked Control Systems: Consensus and Connectivity

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Covers the concept of polynomial characteristic of a matrix and its relation to eigenvalues.

Covers matrix eigenvalues, eigenvectors, and their linear independence.

Covers the analysis of local extrema and Hessians, focusing on the development of limit notations.

Explores properties of matrices, irreducibility, and graph connectivity in networked control systems.

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.