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Parameterized S-Parameter Based Macromodeling With Guaranteed Passivity
This letter presents a novel parametric macromodeling technique for scattering input-output representations parameterized by design variables such as geometrical layout or substrate features. ItExpand
Guaranteed Passive Parameterized Admittance-Based Macromodeling
We propose a novel parametric macromodeling technique for admittance and impedance input-output representations parameterized by design variables such as geometrical layout or substrate features. ItExpand
Compact Behavioral Models of Nonlinear Active Devices Using Response Surface Methodology
This paper presents the response surface methodology in modeling of nonlinear microwave devices. First, different combinations of sampling techniques and types of radial basis functions are evaluatedExpand
Non intrusive Polynomial Chaos-based stochastic macromodeling of multiport systems
TLDR
A novel technique to efficiently perform the variability analysis of electromagnetic systems using a non-intrusive Polynomial Chaos approach with the Vector Fitting algorithm to describe the system variability features with accuracy and efficiency. Expand
Parametric macromodeling based on amplitude and frequency scaled systems with guaranteed passivity
We propose a novel parametric macromodeling method for systems described by scattering parameters, which depend on multiple design variables such as geometrical layout or substrate features. It isExpand
Multipoint Full-Wave Model Order Reduction for Delayed PEEC Models With Large Delays
The increase of operating frequencies requires 3-D electromagnetic (EM) methods, such as the partial element equivalent circuit (PEEC) method, for the analysis and design of high-speed circuits. VeryExpand
Performance study of multi-fidelity gradient enhanced kriging
Multi-fidelity surrogate modelling offers an efficient way to approximate computationally expensive simulations. In particular, Kriging-based surrogate models are popular for approximatingExpand
Variance Weighted Vector Fitting for Noisy Frequency Responses
This letter presents a modification of the Vector Fitting algorithm to estimate rational models of frequency responses affected by noise, e.g. in the case of measured data. It is based on the use ofExpand
Passivity-Preserving Parametric Macromodeling by Means of Scaled and Shifted State-Space Systems
We propose a novel parametric macromodeling method for systems described by admittance and impedance representations, which depend on multiple design variables such as geometrical layout or substrateExpand
A constrained multi-objective surrogate-based optimization algorithm
TLDR
A multi-objective constrained optimization algorithm is presented in this paper which makes use of Kriging models, in conjunction with multi- objective probability of improvement (PoI) and probability of feasibility (PoF) criteria to drive the sample selection process economically. Expand
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