VISA: versatile impulse structure approximation for time-domain linear macromodeling

Chi-Un Lei, Ngai Wong

Abstract: We develop a rational function macromodeling algorithm named VISA (Versatile Impulse Structure Approximation) for macromodeling of system responses with (discrete) time-sampled data. The ideas of Walsh theorem and complementary signal are introduced to convert the macromodeling problem into a non-pole-based Steiglitz-McBride (SM) iteration (a class of first- and second-order interpolations) without initial guess and eigenvalue computation. We demonstrate the fast convergence and the versatile macromodeling requirement adoption through a P-norm approximation expansion, using examples from practical data.