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Showing papers by "Thales (Netherlands) published in 2011"


Book ChapterDOI
01 Jan 2011
TL;DR: This chapter introduces CRISP, presents the concepts, and outlines the preliminary results of a running project.
Abstract: The Cutting edge Reconfigurable ICs for Stream Processing (CRISP) project aims to create a highly scalable and dependable reconfigurable system concept for a wide range of tomorrow’s streaming DSP applications. Within CRISP, a network-on-chip based many-core stream processor with dependability infrastructure and run-time resource management is devised, implemented, and manufactured to demonstrate a coarse-grained core-level reconfigurable system with scalable computing power, flexibility, and dependability. This chapter introduces CRISP, presents the concepts, and outlines the preliminary results of a running project.

20 citations


Journal ArticleDOI
TL;DR: It is demonstrated how UT can be used to efficiently identify the parameters which contribute significantly to the uncertainty in cable coupling and then to provide a measure of the probability distribution for the multivariate problem.
Abstract: This work presents the use of unscented transforms (UT) for the description of statistical uncertainty in electromagnetic coupling between cables. UT greatly reduce the computational burden for the statistical analysis of nonlinear problems compared with more traditional approaches such as the Monte Carlo technique. Coupling between cables has a nonlinear parameter dependence and has a high variability due to the variability in the cable braid manufacture and the highly variable nature of cable layout. Therefore, cable coupling can only be defined within statistical limits. First, it is shown that by analyzing the resonances the important features of maximum coupling and the point of maximum coupling can be characterized. It is then demonstrated how UT can be used to efficiently identify the parameters which contribute significantly to the uncertainty in cable coupling and then to provide a measure of the probability distribution for the multivariate problem.

4 citations