We present a least-squares (LS) algorithm for rational function macromodeling of port-to-port responses with discrete-time sampled data. The core routine involves over-determined equations and Altering operation, and avoids numerical-sensitive calculation and initial pole assignment. We demonstrate the fast computation and excellent accuracy and robustness, even with noisy data, in stable response approximation.
['Chi-Un Lei', 'Hing-Kit Kwan', 'Yansong Liu', 'Ngai Wong']
Efficient linear macromodeling via least-squares response approximation