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This lecture covers the computation of sparse matrices in multivariable control, focusing on the projection onto sparsity subspaces. The instructor explains how to compute the projection, the convergence of the PGD algorithm, and the implications of sparse matrices in distributed control scenarios. The lecture also delves into the optimization of locally optimal controllers using sparse matrices and the challenges in finding stabilizing solutions. Various examples and exercises are provided to illustrate the concepts discussed.