Electrical Performance of Electronic Packaging,
DOI: 10.1109/epep.2002.1057936
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A fast algorithm and practical considerations for passive macromodeling of measured/simulated data

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Cited by 41 publications
(54 citation statements)
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“…In reference to linear time-invariant passive components/circuits, extracted macro-models based on rational function approximations could face stability and passivity preservation problems. The stability condition imposes that the poles of the extracted macro-model lie on the left half-part of the s-plane [6] while, the passivity preservation condition ensures, for a passive circuit, to not generate energy (amplification/oscillation phenomena) [19][20][21][22] as discussed in the Appendix.…”
Section: Iiibroad-band Spice Extraction Methodologymentioning
confidence: 99%
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“…In reference to linear time-invariant passive components/circuits, extracted macro-models based on rational function approximations could face stability and passivity preservation problems. The stability condition imposes that the poles of the extracted macro-model lie on the left half-part of the s-plane [6] while, the passivity preservation condition ensures, for a passive circuit, to not generate energy (amplification/oscillation phenomena) [19][20][21][22] as discussed in the Appendix.…”
Section: Iiibroad-band Spice Extraction Methodologymentioning
confidence: 99%
“…In the case of extracted synthesis elements given in Table I Such criteria (A-10) and (A-11) are easy to verify for passivity preservation checking, however enforcing passivity once the criteria is violated requires efficient techniques. In [19][20] a post-processing perturbation technique combined with linearization procedure is used for passivity enforcement while in [22] perturbation of Hamiltonian matrix is proposed.…”
mentioning
confidence: 99%
“…The vector-fitting algorithm [9] followed by passive check and compensation algorithm [10] is used to generate the positive-real closed form of the p.u.l. series impedance matrix and parallel admittance matrix of the lines:…”
Section: Modelmentioning
confidence: 99%
“…Traditionally, modeling of high-speed distributed networks have been based on the assumption that the model parameters are either known constants [1][2][3][4][5][6] or varying in a deterministic fashion [7][8][9]. However, with the constant drive towards greater miniaturization and stricter design criteria, parameter variation of high-speed distributed networks induced by manufacturing processes, temperature variability, and EM environment are random in nature and cannot be studied accurately using deterministic approaches [10].…”
Section: Introductionmentioning
confidence: 99%