Operator-based model-order reduction of linear periodically time-varying systems

Linear periodically time-varying (LPTV) abstractions are useful for a variety of communication and computer subsystems. In this paper, we present a novel operator-based model-order reduction (MOR) algorithm for reducing large LPTV systems to smaller ones, a capability useful for system-level performance analysis. Our procedure is based on generalizing existing matrix-based Krylov-sub-space algorithms to arbitrary function-space operators. Practical benefits of our approach include significantly enhanced algorithm and code modularity, compared to previous LPTV-MOR approaches based on a-priori discretization. We demonstrate the use of the proposed technique on several circuit examples.