Wavelet­-Based Passivity Preserving Model Order Reduction with Adaptive Frequency Selection

Mehboob Alam,  Arthur Nieuwoudt,  Yehia Massoud
Rice University


Model order reduction plays a key role in determining VLSI system performance and fast simulation of interconnect. In this paper, we develop an accurate and provably passive method for model order reduction using adaptive wavelet-based frequency selective projection. We dynamically select interpolation points among the spectral-zeros of a system by applying inexpensive Haar wavelets and performing efficient spectral zero selection. The wavelet-based approach provides an automated means to generate low order models that are accurate in a particular range of frequencies. The results indicate that our approach provides more accurate reduced order models than the spectral zero method with uniform interpolation points and zero-shift and multi-shift Block Arnoldi-based techniques.