Covers basics of matrix theory and graph theory; distributed averaging and consensus methods on graphs; parallel computation of fixed points; basics of optimization; parallel and distributed optimization methods over graphs; convergence analysis. The techniques and methodologies presented in the course are introduced through application setups including Internet of Things, power and energy systems, sensor networks, transportation systems, and social networks. Previously offered as a special topics course. Recommended prerequisites: ECEN 5448 and courses in convex optimization.
