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Research on the relationship between geophysical structural features and earthquakes in Mid-Yunnan and the surrounding area 被引量:1
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作者 Wu Guiju Tan Hongbo +1 位作者 Yang Guangliang Shen Chongyang 《Geodesy and Geodynamics》 2015年第5期384-391,共8页
In this study, we analyzed the gravity and, magnetic characteristics, and the occurrence of a fault zone and discussed the relationships between the two locations. The results reveal that the subsurface structures str... In this study, we analyzed the gravity and, magnetic characteristics, and the occurrence of a fault zone and discussed the relationships between the two locations. The results reveal that the subsurface structures strikes are different compared with those in the research region. In other words, the geophysical advantageous directions from the gravity and magnetic anomalies are not the same as those caused by the surface structures. The local horizontal gradient results from the gravity and magnetic anomalies show that the majority of earthquakes occur along an intense fault zone, which is a zone of abrupt gravity and negative magnetic change, where the shapes match very well. From the distribution of earthquakes in this area, we find that it has experienced more than 11 earthquake events with magnitude larger than Ms7.0. In addition, water development sites such as Jinshajiang, Lancangjiang, and the Red River and Pearl River watersheds have been hit ten times by earthquakes of this magnitude. It is observed that strong earthquakes occur frequently in the Holocene active fault zone. 展开更多
关键词 Gravity anomaly Magnetic anomaly Multi-scale wavelet analysis Tectonics Earthquake 3D sliding average method Geological feature River system
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A primary-secondary background model with sliding window PCA algorithm
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作者 Hailong ZHU Peng LIU +1 位作者 Jiafeng LIU Xianglong TANG 《Frontiers of Electrical and Electronic Engineering in China》 CSCD 2011年第4期528-534,共7页
Rain and snow seriously degrade outdoor video quality.In this work,a primary-secondary background model for removal of rain and snow is built.First,we analyze video noise and use a sliding window sequence principal co... Rain and snow seriously degrade outdoor video quality.In this work,a primary-secondary background model for removal of rain and snow is built.First,we analyze video noise and use a sliding window sequence principal component analysis de-nosing algorithm to reduce white noise in the video.Next,we apply the Gaussian mixture model(GMM)to model the video and segment all foreground objects primarily.After that,we calculate von Mises distribution of the velocity vectors and ratio of the overlapped region with referring to the result of the primary segmentation and extract the interesting object.Finally,rain and snow streaks are inpainted using the background to improve the quality of the video data.Experiments show that the proposed method can effectively suppress noise and extract interesting targets. 展开更多
关键词 sliding window sequence principal component analysis primary-secondary background model removal of rain and snow Gaussian mixture model(GMM)
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