Lectures related to Networked Control Systems: Convergence Rate and Digraphs

Explores the design of graph weights for consensus and applications in sensor networks.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Explores consensus algorithms in digraphs, focusing on scenarios where the digraph is not strongly connected.

Covers handling network data, types of graphs, centrality measures, and properties of real-world networks.

Explores strongly connected components and condensation digraphs in networked control systems, demonstrating their practical implications.

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