In MIMO wireless communication systems, when more and more antennas are packed into spatiallylimited receive region, the antenna saturation phenomenon will appear. Moreover, the electromagnetic interactions among ante...In MIMO wireless communication systems, when more and more antennas are packed into spatiallylimited receive region, the antenna saturation phenomenon will appear. Moreover, the electromagnetic interactions among antennas will also become stronger and stronger and affect the antenna saturation effect considerably. Despite this, few studies consider these two effects jointly. The effects of antenna saturation are investigated under the consideration of mutual coupling, thus a more practical and physically meaningful result can be obtained.展开更多
1.Difficulties of conventional seismic studies on earthquake source parameters Earthquake source parameters,including magnitude,location,focal mechanism,rupture process are key factors for understanding seismogenic en...1.Difficulties of conventional seismic studies on earthquake source parameters Earthquake source parameters,including magnitude,location,focal mechanism,rupture process are key factors for understanding seismogenic environment,mitigating seismic hazards,estimating earthquake triggering,and tectonic analysis.Traditionally,source parameters are determined by seismological methods.For example,Fang L H et al.（2014）relocated the 2012 Ms6.6 Xinjiang Xinyuan earthquake sequence using local seismograms based on the double difference method,展开更多
This paper presents a relevance vector regression(RVR) based on parametric approach to the bias field estimation in brain magnetic resonance(MR) image segmentation. Segmentation is a very important and challenging tas...This paper presents a relevance vector regression(RVR) based on parametric approach to the bias field estimation in brain magnetic resonance(MR) image segmentation. Segmentation is a very important and challenging task in brain analysis,while the bias field existed in the images can significantly deteriorate the performance.Most of current parametric bias field correction techniques use a pre-set linear combination of low degree basis functions, the coefficients and the basis function types of which completely determine the field. The proposed RVR method can automatically determine the best combination for the bias field, resulting in a good segmentation in the presence of noise by combining with spatial constrained fuzzy C-means(SCFCM)segmentation. Experiments on simulated T1 images show the efficiency.展开更多
基金the National High Technology Research and Development Program of China (2002AA123032).
文摘In MIMO wireless communication systems, when more and more antennas are packed into spatiallylimited receive region, the antenna saturation phenomenon will appear. Moreover, the electromagnetic interactions among antennas will also become stronger and stronger and affect the antenna saturation effect considerably. Despite this, few studies consider these two effects jointly. The effects of antenna saturation are investigated under the consideration of mutual coupling, thus a more practical and physically meaningful result can be obtained.
文摘1.Difficulties of conventional seismic studies on earthquake source parameters Earthquake source parameters,including magnitude,location,focal mechanism,rupture process are key factors for understanding seismogenic environment,mitigating seismic hazards,estimating earthquake triggering,and tectonic analysis.Traditionally,source parameters are determined by seismological methods.For example,Fang L H et al.（2014）relocated the 2012 Ms6.6 Xinjiang Xinyuan earthquake sequence using local seismograms based on the double difference method,
基金National Natural Science Foundation of Chinagrant number:10971190+1 种基金National Natural Science Foundation of Chinagrant number:11001239 and 11101365
文摘This paper presents a relevance vector regression(RVR) based on parametric approach to the bias field estimation in brain magnetic resonance(MR) image segmentation. Segmentation is a very important and challenging task in brain analysis,while the bias field existed in the images can significantly deteriorate the performance.Most of current parametric bias field correction techniques use a pre-set linear combination of low degree basis functions, the coefficients and the basis function types of which completely determine the field. The proposed RVR method can automatically determine the best combination for the bias field, resulting in a good segmentation in the presence of noise by combining with spatial constrained fuzzy C-means(SCFCM)segmentation. Experiments on simulated T1 images show the efficiency.
