Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framewor...Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framework has been recognized as an effective way to achieve dynamic spectrum access.From the perspective of spectrum auction,multi-band multi-user auction provides a new challenge for spectrum management.This paper proposes an auction framework based on location information for multi-band multi-user spectrum allocation.The performance of the proposed framework is compared with that of traditional auction framework based on a binary interference model as a benchmark.Simulation results show that primary users will obtain more total system revenue by selling their idle frequency bands to secondary users and the spectrum utilization of the proposed framework is more effective and fairer.展开更多
Traditional multi-band frequency selective surface （FSS） approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To so...Traditional multi-band frequency selective surface （FSS） approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To solve this problem, an approach of combining elements in different period to build a hybrid array is presented. The results of series of numerical simulation show that multi-periodicity combined element FSS, which are designed using this approach, usually have much weaker grating lobes than the traditional FSS. Furthermore, their frequency response can be well predicted through the properties of their member element FSS. A prediction method for estimating the degree of expected grating lobe energy loss in designing multi-band FSS using this approach is provided.展开更多
城市综合能源系统(urban integrated energy system,UIES)作为城市能源生产、运输、消费的载体,其运行中需要具备充足的灵活性来应对各种不确定波动。从灵活性的定义出发,该文提出基于不确定量波动范围的灵活性调度指标。为降低传统区...城市综合能源系统(urban integrated energy system,UIES)作为城市能源生产、运输、消费的载体,其运行中需要具备充足的灵活性来应对各种不确定波动。从灵活性的定义出发,该文提出基于不确定量波动范围的灵活性调度指标。为降低传统区间数在描述不确定量时由于概率信息丢失而导致的决策保守性,提出采用考虑相关性的多带区间数(multi-band interval number,MBIN)描述不确定量的方法,并通过历史数据和插值法得到连续的累积分布函数。提出以运行成本最小和可容纳室外温度和光照强度不确定波动范围最大的UIES多目标区间优化调度模型。采用区间可能度方法处理含有传统区间数和考虑相关性的MBIN的约束条件,将原问题转化为确定性多目标混合整数线性规划问题。通过一种直接求解多目标优化问题折中最优解的方法,将此问题进一步转化为可以高效求得折中最优解的单目标混合整数线性规划问题。最后,通过一个含有农业-工业-商业园区的实际UIES的算例分析,结果验证所提出模型和求解方法的正确有效性。展开更多
多波段图像目标检测识别是重要的多模态基础任务之一,旨在通过不同传感器的成像特性补充完善目标特征来提高目标感知效果,对提升交通、医疗、军事等领域智能化程度具有重要的现实意义。针对目标检测识别中广泛存在的因光照、遮挡、复杂...多波段图像目标检测识别是重要的多模态基础任务之一,旨在通过不同传感器的成像特性补充完善目标特征来提高目标感知效果,对提升交通、医疗、军事等领域智能化程度具有重要的现实意义。针对目标检测识别中广泛存在的因光照、遮挡、复杂背景导致的检测识别效果不佳的问题,提出一种动态自适应聚合的可见光红外图像目标检测识别方法。通过设计通道注意力混合和二次动态权重连接的动态聚合结构以及语义空间信息交互的多路径扩展Neck结构,充分挖掘多波段图像的互补性,来提升困难场景下多波段图像目标融合检测的平均准确率。经公开数据集测试,相较于不采用动态聚合结构和多路径扩展Neck结构的对比模型,该方法的平均准确率(mean Average Precision,mAP)提高4个百分点以上。展开更多
基金supported by the Beijing Natural Science Foundation of China (4102050)
文摘Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framework has been recognized as an effective way to achieve dynamic spectrum access.From the perspective of spectrum auction,multi-band multi-user auction provides a new challenge for spectrum management.This paper proposes an auction framework based on location information for multi-band multi-user spectrum allocation.The performance of the proposed framework is compared with that of traditional auction framework based on a binary interference model as a benchmark.Simulation results show that primary users will obtain more total system revenue by selling their idle frequency bands to secondary users and the spectrum utilization of the proposed framework is more effective and fairer.
基金supported by the National Natural Science Foundation of China(90305026).
文摘Traditional multi-band frequency selective surface （FSS） approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To solve this problem, an approach of combining elements in different period to build a hybrid array is presented. The results of series of numerical simulation show that multi-periodicity combined element FSS, which are designed using this approach, usually have much weaker grating lobes than the traditional FSS. Furthermore, their frequency response can be well predicted through the properties of their member element FSS. A prediction method for estimating the degree of expected grating lobe energy loss in designing multi-band FSS using this approach is provided.
文摘多波段图像目标检测识别是重要的多模态基础任务之一,旨在通过不同传感器的成像特性补充完善目标特征来提高目标感知效果,对提升交通、医疗、军事等领域智能化程度具有重要的现实意义。针对目标检测识别中广泛存在的因光照、遮挡、复杂背景导致的检测识别效果不佳的问题,提出一种动态自适应聚合的可见光红外图像目标检测识别方法。通过设计通道注意力混合和二次动态权重连接的动态聚合结构以及语义空间信息交互的多路径扩展Neck结构,充分挖掘多波段图像的互补性,来提升困难场景下多波段图像目标融合检测的平均准确率。经公开数据集测试,相较于不采用动态聚合结构和多路径扩展Neck结构的对比模型,该方法的平均准确率(mean Average Precision,mAP)提高4个百分点以上。
