Non intrusive polynomial chaos-based stochastic macromodeling of multiport systems

We present a novel technique to efficiently perform the variability analysis of electromagnetic systems. The proposed method calculates a Polynomial Chaos-based macromodel of the system transfer function that includes its statistical properties. The combination of a non-intrusive Polynomial Chaos approach with the Vector Fitting algorithm allows to describe the system variability features with accuracy and efficiency. The results of the variability analysis performed with the proposed method are verified by means of comparison with respect to the standard Monte Carlo analysis

Efficient time-domain modeling and simulation of passive bandpass systems

In communication systems, the signals of interest are often amplitude and/or phase modulated ones. In this framework, the baseband equivalent signals and systems representation is usually adopted to simulate the digital parts of communication systems in an efficient manner. This contribution extends the applicability of such representation to RF/analog devices, leading to a common and efficient modeling and simulation framework. In particular, the proposed method can build half-size models compared to existing approaches, and allows one to choose the simulation time step according to the bandwidth of the modulating signals rather than the carrier frequency, thereby significantly speeding up the simulation procedure. The novel proposed method is validated via a suitable application example

Time-domain parametric sensitivity analysis of multiconductor transmission lines

We present a new parametric macromodeling technique for lossy and dispersive multiconductor transmission lines (MTLs). This technique can handle design parameters, such as substrate or geometrical layout features, and provide time-domain sensitivity information for voltage and currents at the ports of the lines. It is based on a recently introduced spectral approach for the analysis of lossy and dispersive MTLs [1], [2] and it is suited to generate state-space models and synthesize equivalent circuits, which can be easily embedded into conventional SPICE-like solvers. Parametric macromodels which provide sensitivity information are well suited for design space exploration, design optimization and crosstalk analysis. A numerical example validates the proposed approach in both frequency and time domain

Comprehensive and modular stochastic modeling framework for the variability-aware assessment of Signal Integrity in high-speed links

This paper presents a comprehensive and modular modeling framework for stochastic signal integrity analysis of complex high-speed links. Such systems are typically composed of passive linear networks and nonlinear, usually active, devices. The key idea of the proposed contribution is to express the signals at the ports of each of such system elements or subnetworks as a polynomial chaos expansion. This allows one to compute, for each block, equivalent deterministic models describing the stochastic variations of the network voltages and currents. Such models are synthesized into SPICE-compatible circuit equivalents, which are readily connected together and simulated in standard circuit simulators. Only a single circuit simulation of such an equivalent network is required to compute the pertinent statistical information of the entire system, without the need of running a large number of time-consuming electromagnetic circuit co-simulations. The accuracy and efficiency of the proposed approach, which is applicable to a large class of complex circuits, are verified by performing signal integrity investigations of two interconnect examples

PDE4 inhibitors as potential therapeutic agents in the treatment of COPD-focus on roflumilast

Chronic obstructive pulmonary disease is characterized by a rapid decline in lung function due to small airway fibrosis, mucus hypersecretion and emphysema. The major causative factor for COPD is cigarette smoking that drives an inflammatory process that gives rise to leukocyte recruitment, imbalance in protease levels and consequently matrix remodeling resulting in small airway fibrosis and loss of alveolar tissue. Current drug treatment improves symptoms but do not alter the underlying progression of this disease. The failure of anti-inflammatory drugs like glucocorticosteroids to have a major impact in this disease has hastened the need to develop novel therapeutic strategies. Phosphodiesterase (PDE)4 inhibitors are novel anti-inflammatory drugs that have recently been show to document clinical efficacy in this disease, although their utility is hampered by class related side-effects of nausea, emesis and diarrhea. Whilst it is not yet clear whether such drugs will prevent emphysema, this is a distinct possibility provided experimental observations from preclinical studies translate to man. This review will discuss the current standing of PDE4 inhibitors like roflumilast as novel treatments for COPD and the potential for developing nonemetic anti-inflammatory drugs

Time-domain analysis of RF and microwave autonomous circuits by vector fitting-based approach

This work presents a new method for the analysis of RF and microwave autonomous circuits directly in the time-domain, which is the most effective approach at simulation level to evaluate nonlinear phenomena. For RF and microwave autonomous circuits, time-domain simulations usually experiment convergence problems or numerical inaccuracies due to the presence of distributed elements, preventing de-facto their use. The proposed solution is based on the Vector Fitting algorithm applied directly at circuit level. A case study relative to a RF hybrid oscillator is presented for practical demonstration and evaluation of performance reliability of the proposed method