Stochastic prediction of wire coupling interference

Many EMC analyses of complex systems frequently result in a statement that insufficient knowledge is available to describe accurately the internal relationships of the system's components. This lack of information precludes any rigorous deterministic prediction and, in principle, requires that we express the uncertainties within the model. This paper shows the practical feasibility of stochastic prediction, as an alternative to deterministic simulation, applied to a class of EMC problems intrinsically affected by randomness. The evaluation of the crosstalk in standard cable bundles, in which several wires are tightly and randomly wrapped together, is the concrete problem that we investigate in this context. We developed a technique based on solving the nonuniform multiconductor transmission lines (MTL) for many randomly generated wires' geometries to obtain many crosstalk samples for a single frequency. Finally we validated the method, setting up a case study with published experimental result

Parametric Macromodels of Differential Drivers and Receivers

This paper addresses the modeling of differential drivers and receivers for the analog simulation of high-speed interconnection systems. The proposed models are based on mathematical expressions, whose parameters can be estimated from the transient responses of the modeled devices. The advantages of this macromodeling approach are: improved accuracy with respect to models based on simplified equivalent circuits of devices; improved numerical efficiency with respect to detailed transistor-level models of devices; hiding of the internal structure of devices; straightforward circuit interpretation; or implementations in analog mixed-signal simulators. The proposed methodology is demonstrated on example devices and is applied to the prediction of transient waveforms and eye diagrams of a typical low-voltage differential signaling (LVDS) data link

Validation by Measurements of a IC Modeling Approach for SiP Applications

The growing importance of signal integrity (SI) analysis in integrated circuits (ICs), revealed by modern systemin-package methods, is demanding for new models for the IC sub-systems which are both accurate, efficient and extractable by simple measurement procedures. This paper presents the contribution for the establishment of an integrated IC modeling approach whose performance is assessed by direct comparison with the signals measured in laboratory of two distinct memory IC devices. Based on the identification of the main blocks of a typical IC device, the modeling approach consists of a network of system-level sub-models, some of which with already demonstrated accuracy, which simulated the IC interfacing behavior. Emphasis is given to the procedures that were developed to validate by means of laboratory measurements (and not by comparison with circuit-level simulations) the model performance, which is a novel and important aspect that should be considered in the design of IC models that are useful for SI analysi

Reliable Eye-Diagram Analysis of Data Links via Device Macromodels

This paper addresses the impact of device macromodels on the accuracy of signal integrity and performance predictions for critical digital interconnecting systems. It exploits nonlinear parametric models for both single-ended and differential devices, including the effects of power supply fluctuations and receiver bit detection. The analysis demonstrates that the use of well-designed macromodels dramatically speeds up the simulation as well it preserves timing accuracy even for long bit sequences

Machine Learning for the Uncertainty Quantification of Power Networks

This letter addresses the uncertainty quantification of a power network and is based on surrogate models built via Machine Learning techniques. Specifically, the least-square support vector machine regression is combined with the principal component analysis to generate a compressed surrogate model capable of predicting all the nodal voltages of the network as a function of the uncertain electrical parameters of the transmission lines. The surrogate model is built from a limited number of system responses provided by the computational model. The power flow analysis of the benchmark IEEE-118 bus system with 250 parameters is considered as a test case. The performance of the proposed modeling strategy in terms of accuracy, efficiency and convergence, are assessed and compared with those of an alternative surrogate model based on a sparse implementation of the polynomial chaos expansion. The results of a Monte Carlo simulation are used as reference in the above comparison

Radiometric Active Indoor Imaging in the W-Band

Millimeter wave passive imaging systems constitute a good compromise between resolution and penetration depth for a variety of imaging applications. In an outdoor scenario, the cold sky radiation, interacting with the reflectivity characteristics of the targets, constitutes the main source of contrast in the acquired images. In indoor applications such a source is not available, and higher thermal sensitivity is required. Alternatively, one has to provide an artificial illumination to the scene in order to increase its dynamic range. The implementation of an active source for a passive radiometer can, under certain conditions, increase the contrast of the images acquired and add extra information to the measurement. With such a setup, outdoor systems can be used for indoor observations (the absence of cold sky radiation is compensated with active illumination). The subject of our study is to better understand which kind of source and which setup can provide a diffuse illumination over the targets. This topic was investigated by conducting observations of various indoor scenes with two radiometers in the W-Band, using noise and continuous wave (CW) sources as illumination. In this paper we present the results achieved and our conclusions in order to provide an efficient illumination for indoor environment

National Commission on Social, Emotional, and Academic Development: A Policy Agenda in Support of How Learning Happens

Policy can play an essential role in moving efforts to support the whole learner from the periphery to the mainstream of American education, and from the realm of ideas to implementation. This document is rooted in the belief that policy should create enabling conditions for communities to implement locally crafted practices that drive more equitable outcomes by supporting each and every student's social, emotional, and academic development