A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network

This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters.     

红外成像制导中的三维目标识别

首先介绍了随机方位观察模型 ,在此基础上得到图像中的角度大小与目标模型中角度大小的对应关系 ,提出了图像中的角度大小的概率密度函数 ,然后根据最大似然比准则得到三维目标识别的统计决策规则 ,并应用该规则去识别红外成像制导中的几种具体目标 ,取得了比较好的识别效果 ,证明了所提方法在红外成像制导中的三维目标识别的有效性。     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.     

基于家庭关联关系识别模型的电信融合套餐营销

本文回顾了中国电信承接原联通C网以来的全业务融合套餐现状,分析了识别原有CDMA手机号码与固定电话号码的关联关系对于电信融合套餐营销的意义,详细描述了利用决策树算法来构建家庭关联关系识别模型的过程和方法,并简要介绍了如何应用模型结果进行融合套餐的针对性营销.     

基于序列检测的块判决辅助Turbo均衡器

该文针对高斯分布假设条件下逐符号检测均衡器的不足,提出了一种基于序列检测的块判决辅助Turbo均衡器(Turbo-BDAE)。新算法利用译码全信息估计发送序列,提高了序列估计的可靠性,引入软判决可以降低硬判决引起的错误扩散,同时结合序列检测为均衡器输出的后验概率(APP)估计提供了更可靠的信息。仿真表明,该均衡器在保持相近复杂度的同时,进一步提升了均衡系统性能,优于逐符号LMMSE均衡器和硬反馈BDFE。     

一种低信噪比下的模拟调制信号识别方法

信号调制方式的自动识别是未来软件无线电必须具备的功能之一。本文针对模拟调制方式提出了一种基于决策理论的识别流程,分析了模拟调制识别特征参数的提取。该方法具有计算简单、无需知道信号的先验信息的特点,而且能在低信噪比情况下快速有效地进行调制识别,易于实时应用和工程实现。仿真结果表明,在0dB信噪比条件下,正确识别率能够达到85％以上,性能优于传统的调制识别方法。     

分类挖掘技术在高校人事管理中的应用

探讨分类挖掘技术在高校实际工作中的应用方式与应用领域。以高校人事管理为模型，应用数据挖掘中决策树算法，对高校人力资源数据源中的信息进行分析，发现其中有价值的数据模式，寻找其中存在的关系和规则，对高校人才规划提供比较客观的决策支持。     

信息安全风险评估的模糊多准则决策方法

基于ISO/IEC17799标准建立了一个综合的信息系统风险分析框架,并运用模糊多准则决策(FMCDM)方法计算信息安全风险,根据风险等级矩阵(RLM)对信息资产风险进行级别划分,最终建立评估信息资产相关风险的完整模型。     

基于半马尔科夫决策过程的视频传输拥塞控制算法

针对传输控制协议(TCP, transmission control protocol)的拥塞控制算法未能满足视频传输质量要求的问题,提出了一种基于半马尔科夫决策过程的视频传输拥塞控制算法。首先, 为克服目前基于峰值信噪比的视频质量评估方法实时性低的缺点,设计了一种可在线运行的无参考视频质量评估方法。其次,根据接收端视频质量的反馈,采用半马尔科夫决策过程对拥塞控制进行建模,并通过求解此模型得到拥塞控制参数的调整策略。仿真实验结果表明,与目前典型的拥塞控制算法相比,该算法不但具备更好的TCP友好性,而且有效地提高了解码后视频序列的主观和客观质量。     

基于NCL路径平衡的抗功耗分析方法

由于对路径结构平衡的本质以及设计方法缺乏系统的研究,导致其在实际应用中严重依赖设计者自身的经验,难以推广到各类自动化综合方法中。对实现路径平衡结构的形式化定义及充分条件进行了研究,并给出了证明,进而提出了一种基于改进二元决策图(BDD, binary decision diagram)的零协议逻辑(NCL, null convention logic)异步电路路径平衡扩展方法。该方法能够简便地扩展至各类自动化综合过程中,并能在不改变目标电路特性的前提下,有效实现NCL异步电路的路径平衡结构,抵消由于寄生电容和负载电容差异所造成的密码芯片旁路信息泄露。