Abstract-Broadband macromodeling of large multiport systems by vector fitting can be time consuming and resource demanding when all elements of the system matrix share a common set of poles. This letter presents a robust approach which removes the sparsity of the block-structured least-squares equations by a direct application of the QR decomposition. A 60-port printed circuit board example illustrates that considerable savings in terms of computation time and memory requirements are obtained.

Abstract-An important issue in high-frequency signal integrity prediction is the modeling of the skin effect of thick conductors. A new differential surface admittance concept is put forward allowing to replace the conductor by equivalent electric surface currents and to replace the material of the conductor by the material of the background medium the conductor is embedded in. This new concept is studied in detail for the two-dimensional TM case starting from the Dirichlet eigenfunctions of the cross section. Detailed expressions are derived for the important practical case of a rectangular cross section. Next, the differential surface admittance operator is exploited to determine the resistance and inductance matrices of a set of multiconductor lines. A first set of numerical results provides the reader with some insight into the behavior of the surface admittance matrix. A second set of results demonstrates the correctness and versatility of the new approach to determine inductance and resistance matrices.

The aim of the study was to assess sleep-wake habits and disorders and excessive daytime sleepiness (EDS) in an unselected outpatient epilepsy population. Sleep-wake habits and presence of sleep disorders were assessed by means of a clinical interview and a standard questionnaire in 100 consecutive patients with epilepsy and 90 controls. The questionnaire includes three validated instruments: the Epworth Sleepiness Scale (ESS) for EDS, SA-SDQ for sleep apnea (SA), and the Ullanlinna Narcolepsy Scale (UNS) for narcolepsy. Sleep complaints were reported by 30% of epilepsy patients compared to 10% of controls (p=0.001). The average total sleep time was similar in both groups. Insufficient sleep times were suspected in 24% of patients and 33% of controls. Sleep maintenance insomnia was more frequent in epilepsy patients (52% vs. 38%, p=0.06), whereas nightmares (6% vs. 16%, p=0.04) and bruxism (10% vs. 19%, p=0.07) were more frequent in controls. Sleep onset insomnia (34% vs. 28%), EDS (ESS >or=10, 19% vs. 14%), SA (9% vs. 3%), restless legs symptoms (RL-symptoms, 18% vs. 12%) and most parasomnias were similarly frequent in both groups. In a stepwise logistic regression model loud snoring and RL-symptoms were found to be the only independent predictors of EDS in epilepsy patients. In conclusion, sleep-wake habits and the frequency of most sleep disorders are similar in non-selected epilepsy patients as compared to controls. In epilepsy patients, EDS was predicted by a history of loud snoring and RL-symptoms but not by SA or epilepsy-related variables (including type of epilepsy, frequency of seizures, and number of antiepileptic drugs).

Abstract-A robust multivariate extension of the orthonormal vector fitting technique is introduced for rational parametric macromodeling of highly dynamic responses in the frequency domain. The technique is applicable to data that is sparse or dense, deterministic or a bit noisy, and grid-based or scattered in the design space. For a specified geometrical parameter combination, a SPICE equivalent model can be calculated.

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Abstract-This contribution presents an alternative modeling strategy for the stochastic analysis of high-speed interconnects. The proposed approach takes advantage of the polynomial chaos framework and a fully SPICE-compatible formulation to avoid repeated circuit simulations, therefore alleviating the computational burden associated to traditional sampling-based methods like Monte Carlo. Nonetheless, the technique offers very good accuracy and the opportunity to easily simulate complex interconnect topologies which include lossy and dispersive transmission lines, thus overcoming the limitations of previous publications. Application examples involving the stochastic analysis of onchip and on-board interconnects validate the methodology and conclude the paper.

Abstract-In this paper, a novel stochastic modeling strategy is constructed that allows assessment of the parameter variability effects induced by the manufacturing process of on-chip interconnects. The strategy adopts a three-step approach.

This paper presents a systematic approach for the statistical simulation of nonlinear networks with uncertain circuit elements. The proposed technique is based on spectral expansions of the elements' constitutive equations (I-V characteristics) into polynomial chaos series and applies to arbitrary circuit components, both linear and nonlinear. By application of a stochastic Galerkin method, the stochastic problem is cast in terms of an augmented set of deterministic constitutive equations relating the voltage and current spectral coefficients. These new equations are given a circuit interpretation in terms of equivalent models that can be readily implemented in SPICE-type simulators, as such allowing to take full advantage of existing algorithms and available built-in models for complex devices, like diodes and MOSFETs. The pertinent statistical information of the entire nonlinear network is retrieved via a single simulation. This approach is both accurate and efficient with respect to traditional techniques, such as Monte Carlo sampling. Application examples, including the analysis of a diode rectifier, a CMOS logic gate and a low-noise amplifier, validate the methodology and conclude the paper.