标签分块技术在MPLS标签分配中的设计与应用

在MPLS网络中,数据包被短而定长的标签所封装,并根据标签进行转发。本设计通过对MPLS标签空间按不同业务处理进行分块,并为每个业务内嵌独立的本地标签池,设计并实现了基于标签分块技术的MPLS标签分配技术方案。验证表明,该方案有效提高了MPLS标签的申请释放效率,简化了MPLS各种协议业务的处理流程,增加了报文转发效率。     

一种基于幅度统计矩的MQAM信号分类方法

针对加性高斯白噪声(AWGN)环境下M进制正交幅度调制(MQAM)信号的调制分类,提出了一种基于幅度统计矩的MQAM信号分类法,推导出了用于区分MQAM信号的特征参数表达式。计算机仿真结果与理论分析一致,仿真结果表明,在信噪比不低于5 dB时,该方法的正确识别率可保持在97%以上,证明了该方法的有效性。     

基于空气动力学模型含雷达散射截面观测的联合目标跟踪识别

以地基被动警戒雷达为应用背景,主要监视低空突防来袭目标,利用地面上多个商业广播发射的无线电调频（FM）信号,提出基于空气动力学模型含雷达散射截面（RCS）观测的联合目标跟踪识别技术。该技术使用空气动力学模型来描述目标的平动和转动,并将分类器输出的具体参数传递给跟踪器,实现基于动力学模型的跟踪;同时将RCS包括在观测中,它既可提供主要的分类特征,又可根据跟踪器的输出来预测RCS值。跟踪与分类被紧密结合,充分发挥联合跟踪识别的优势,有效提高目标的跟踪性能和识别概率。运用FEKO电磁仿真软件,实时获得目标的RCS观测值,通过粒子滤波实现联合跟踪识别,搭建了基于FM信号的被动雷达目标跟踪识别仿真平台。仿真结果表明,交互式多模型正则化粒子滤波的跟踪精度和识别概率都要优于交互式多模型粒子滤波。     

多波束干扰系统干扰资源综合管理算法

针对先进战机多波束干扰系统同时干扰多部雷达时的资源管理问题,采用多属性决策 方法建立了战机电子对抗系统威胁等级评估模型,并与神经元模型相结合建立了干扰任务请求模 型;针对干扰资源的限制,对目标雷达进行分类,当需要且能够干扰的雷达数目超出干扰波束数目 时,建立了干扰任务整合模型,并采用C-means 算法对模型进行求解;最后提出了多波束干扰系统 同时干扰多部雷达时的资源管理算法。对目标进行分类和对干扰任务进行整合可以提高多波束干 扰系统的效率,提升干扰系统的智能化水平。     

基于加权特征融合的 SAR 图像目标分类方法

针对现有分类器对 SAR 图像分类正确率不高的问题,考虑到单一的特征很难完全描述 SAR 目标,并且单一的分类器识别率有限,提出了一种基于加权特征融合的图像分类方法,采用多种特征来描述目标,并且用多个分类器同时对目标识别。实验结果显示,提出的方法能够达到较高的分类正确率,证明了该方法的有效性。     

Detection and Classification of Small Traffic Signs Based on Cascade Network

Research on the traffic sign detection is significant for driverless technology,which provides useful navigation information.Existing object detection methods are only applicable to large-size objects or small-scale specific types of traffic signs,and the performance of detecting traffic signs in street views is not adequate.In this regard,we propose a method to detect and classify small traffic signs by constructing a cascaded network.Specifically,the RetinaNet network is adopted firstly to integrate multi-layer information to identify small traffic signs in traffic scene images.The focal loss function is used to balance the biased distribution of traffic sign categories.Then,a two-class network is cascaded after the RetinaNet,which helps identify valid traffic signs from the first-stage prediction results.Experiments show that our cascaded network structure could achieve the balance of different categories of predictions and an improvement in precision and recall.     

Higher-order moments for musical genre classification

This paper presents a study on the performance of the higher-order moments for musical genre classification. Especially the skewness and the kurtosis of the octave-scale subbands are considered. Experimental results on the widely used music datasets show that the higher-order moment features can improve classification accuracy when combined with the conventional lower-order moment features.     

Per-pixel classification of clouds from whole sky HDR images

Accurately identifying cloud types in images has multiple uses from meteorological science to computer graphics, especially as clouds are a major factor influencing atmospheric radiative transport. Understanding which cloud types are present in an image is typically performed on a coarse scale, where cloud types are identified per image, but do not permit a finer, per-pixel granularity of labelling cloud types. This paper presents a novel approach which solves this problem via a per-pixel classification method for identifying cloud types based on High Dynamic Range imagery of skies. The proposed method requires minimal labelling of the training data, and utilizes a hierarchical patch-based feature extraction technique which describes the statistical and structural features about regions of the image. This enables the extraction of representative feature vectors which are used for subsequent labelling. This approach is the first to produce a per-pixel classification of cloud types from a single image, with an accuracy of 84%. Additionally, when applied to whole sky cloud classification, our results produce a 98.3% accuracy, which is competitive with the state-of-the-art.     

燃煤飞灰的显微颗粒类型与显微结构特征

利用光学显微镜和扫描电子显微镜对不同燃煤煤种和锅炉类型电厂飞灰进行观察研究,建立了燃煤飞灰微颗粒的系统分类方案,并揭示出各类颗粒的显微结构特征,首先根据物质成分将飞灰分出硅铝质,铁质,钙质和炭粒4个组,然后根据微观形貌和内部结构分出16种显微颗粒类型。研究发现空心微珠和子母珠是飞灰中普遍存在的显微颗粒类型,不仅广泛分布于不同粒级的硅铝质颗粒中,而且常见于钙质和铁质颗粒中,发现并命名了多孔微珠这一新的显微颗粒类型;在多种颗粒中广泛分布的次级细小灰球的发现,为飞灰显微结构的成因研究提供了科学依据。