Abstract
This paper presents a macromodeling technique for modeling distributed circuits characterized by noisy frequency-domain data. The proposed method is based on an iterative Loewner matrix (LM) approach. Using the LM approximation of previous iterations, the singular values and orthonormal matrices of the Loewner pencil are made to be more accurate. This approach is shown to minimize the biasing effect of the noisy data due to the nonlinearity of the singular value decomposition operation, resulting in more accurate poles and residues. Numerical examples illustrate that for noisy frequency-domain data, the proposed algorithm creates more accurate macromodels when compared with the traditional LM approach.
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