Upper bounds for Fourier transforms of exponential functions

Meaningful upper bounds for the Fourier transform of polynomial exponential functions are often hard to come by. Regarding Fourier transforms of rational exponential functions, which are of importance, for example in Campbell's sampling theorem, the purpose of finding significant upper bounds is an even more demanding exercise. In this article, we propose a new approach in order to obtain significant upper bounds for Fourier transforms of general exponential functions. The technique is shown to allow further generalization in order to deal with Fourier-like integrals and rational exponential integrals

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. It is able to build accurate multivariate macromodels that are stable and passive in the entire design space. An efficient combination of rational identification and interpolation schemes based on a class of positive interpolation operators, ensures overall stability and passivity of the parametric macromodel. Numerical examples validate the proposed approach on practical application cases