Microelectronics Colloquium

Sparsity-constrained Linear Dynamical Systems

Geethu Joseph

Abstract: At the intersection of control engineering and signal processing sits the upcoming field of sparse control and state estimation of linear dynamical systems. It deals with linear dynamical systems with control inputs having a few nonzero entries compared to their dimensions. Constraining the inputs to be sparse is often necessary to select a small subset of the available sensors or actuators at each time instant due to energy, bandwidth, or physical network constraints. Bringing together research from classical control theory and compressed sensing, the talk presents a comprehensive overview and critical insights into the conceptual foundations of sparsity-constrained systems, including the formulation, theory, and algorithms. We look at the concrete example of a budget-constrained external agent controlling the opinion of a social network.

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