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Aiming at the problem of fault detection for satellite communication system, a prediction method based on Gaussian mixture model is proposed. Firstly, the observation sequence is collected by modem as well as frequency conversion equipment. Then feature parameters are extracted after pre-processing. The expectation maximum algorithm is applied to train the Gaussian mixture model. The posterior probabilities...
Crowd understanding has drawn increasing attention from the computer vision community, and its progress is driven by the availability of public crowd datasets. In this paper, we contribute a large-scale benchmark dataset collected from the Shanghai 2010 World Expo. It includes $2630$ annotated video sequences captured by $245$ surveillance cameras, far larger than any public dataset. It covers a large...
Artificial neural networks (ANNs) have been applied as an efficient machine-learning tool to model many complex electromagnetic problems recently. This paper gives a comprehensive description on fast extraction of the extrinsic capacitance for 3D FinFET transistors using Q3D with different sizes. This extraction method is later coupled with artificial neural networks to form a controllable model with...
Factor analysis is mainly by extracting the compact representations of speakers' utterances, which are referred to as i-vectors. A low new space called total variability space, which is speaker and channel dependent is trained in the modeling. During the experiments, channel compensation approaches are used to remove the interference included by i-vectors. They are respectively are Nuisance Attribute...
As the better generalization ability of clusterer ensemble methods, they are widely applied to diverse domains. But now many challenges still exist. One of the drawbacks of the ensemble is, ignoring the valuable information contained in the process of training component clusterers. This paper explores a new ensemble method for cluster analysis based on dynamic cooperation, and this method adjusts...
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