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During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational performance in the reduction process. However, moment-matching methods based on the ordinary Krylov subspace are usually inadequate to accurately approximate the original circuit behaviour. In this paper, we present a moment-matching method which is based on the extended Krylov subspace and exploits the superposition property in order to deal with many terminals. The proposed method can handle large-scale regular and singular circuits, and generate accurate and efficient reduced-order models for circuit simulation. Experimental results on industrial IBM power grid benchmarks demonstrate that our method achieves an error reduction up to 83.69% over a standard Krylov subspace technique.

Exploiting Extended Krylov Subspace for the Reduction of Regular and Singular Circuit Models