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the method Singular Spectrum Entropy Analysis (SSEA) studies the complexity and irregular extent of Partial Discharge (PD) signals but cannot fully reflect the intrinsic nonlinear characteristic. In this paper, we apply higher-order statistics to substituting for the co-variance matrix and introduce the Ensemble Empirical Mode Decomposition theory (EEMD) to realize multi-scale as well. The signal...
In complex biological systems, the hypothesis that bio-diversity contributes to stability or robustness is an active debate. The FP7 DIVERSIFY project tests whether this hypothesis holds for software systems, and explores the use of diversity as a heuristic to increase robustness in self-adaptive architectures. Inspired by Ecology, we present here a technique to evaluate diversity of software architectures...
Various services are now available in the Cloud, ranging from turnkey databases and application servers to high-level services such as continuous integration or source version control. To stand out of this diversity, robustness of service compositions is an important selling argument, but which remains difficult to understand and estimate as it does not only depend on services but also on the underlying...
This paper addresses the problem of change detection in high-resolution multitemporal synthetic aperture radar (SAR) images. We propose to use Jensen–Shannon divergence (JSD) to measure the dissimilarity of the two scenes acquired at different times for deriving the difference map (DM). We figure out this divergence in a nonparametric way by introducing a direct density ratio estimation, making the...
It is difficult to express accurately nonlinear characteristics of the bulb turbogenerators with mathematical model. The artificial neural network has more characteristics, such as self-learning, adaptive, distributed parallel, fault-tolerance, memory functions and so on. This paper presents the characteristics of neural network to model for bulb turbogenerators. The results obtained from the nonlinear...
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