Lectures related to Networked Control Systems: Challenges and Opportunities

Explores coordination in networked control systems, graph theory, and consensus algorithms.

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

Explores the application of matrices and eigendecompositions in networks.

Explores graph theory, stochastic matrices, consensus algorithms, and spectral properties in networked control systems.

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

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Explores Laplacian flow, heat equation analogies, and microgrid networked controllers.

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

Explores Cheeger's inequalities for random walks on graphs and their implications.

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Explores coordination among agents in networked control systems through graph theory and real-world examples.

Covers graphical models for probability distributions and factor graphs representation.

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

Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

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

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

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

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

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.