简介：Dempster-Shaferevidencetheory(DStheory)iswidelyusedinbrainmagneticresonanceimaging(MRI)segmentation,duetoitsefficientcombinationoftheevidencefromdifferentsources.Inthispaper,animprovedMRIsegmentationmethod,whichisbasedonfuzzyc-means(FCM)andDStheory,isproposed.Firstly,theaveragefusionmethodisusedtoreducetheuncertaintyandtheconflictinformationinthepictures.Then,theneighborhoodinformationandthedifferentinfluencesofspatiallocationofneighborhoodpixelsaretakenintoconsiderationtohandlethespatialinformation.Finally,thesegmentationandthesensordatafusionareachievedbyusingtheDStheory.ThesimulatedimagesandtheMRIimagesillustratethatourproposedmethodismoreeffectiveinimagesegmentation.

简介：Thephotocurrent-voltagecharacteristicsandphotoelectricsensitivityofa-Si:Hsampleswithslitandcombelectrodesaremeasured.Amethodforcalculatingthechargeintensifyinggainfromthephotoelectricsensitivityisproposed.Theobtainedchargeintensifyinggainofa-Si:Hunderanelectricfieldof105V/cmthroughthismethodisashighas4.3×103.Thegenerationprocessofthechargeintensificationeffectina-Si:Hisdiscussedonthebasisoftheenergyleveldiagram.Andtheproductofelectron’smobilityanditslifetimeiscalculatedfromthemeasuredvaluesofthegains.

简介：提出一种基于均值聚类的车牌定位算法,该算法能避免由于环境的复杂而带来的定位的不确定性。

简介：在现代战争中随着新体制雷达的不断涌现,电磁环境变得越来越复杂,这就对雷达信号分选提出了新的挑战。目前普遍采用的基于直方图统计的信号分选方法越来越不适应现代雷达信号环境。文中将聚类分析技术引入到雷达信号分选中,将蚁群算法和K-Means相结合,互相弥补不足,提出了一种新的雷达信号分选方法,该方法易编程实现,不需要雷达信号的先验知识,适用于处理未知信号的雷达。仿真实验证明分选结果较理想,为雷达信号分选提供了新的思路。