Networked Control Systems: Properties and Connectivity

Related lectures (30)

Page 2 of 3

Introduces Spectral Graph Theory, exploring eigenvalues and eigenvectors' role in graph properties.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Explores consensus in networked control systems through graph weight design and matrix properties.

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Explores pseudorandomness and the Expander Mixing Lemma in the context of d-regular graphs.

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Introduces graph theory basics, graph representation methods, and traversal algorithms like BFS and DFS.

Explores challenges and opportunities in networked control systems, covering LTI systems, delays, packet drops, and consensus.

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.