一个改进的多点乘算法

SPA（Simple Power Analysis）攻击可能通过泄露的信息获取内存受限制的设备（如Smart卡）中的密钥，它是通过区分一次点乘运算中点加运算和倍点运算进行的。抗SPA攻击的点乘算法较多，但对于多点乘算法相关措施较少。interleaving多点乘算法是一个时间和空间效率都非常优秀的多点乘算法。为此提出一种基于interleaving的抗SPA攻击的多点乘算法，新的算法在内存空间消耗和计算速度上较原算法负担增加可以忽略不计，而且能够抗SPA攻击。     

集对分析联系数在学生成绩综评中的应用

用不同方法时学生成绩作综合评定会有不同的评定结果，说明这一过程有不确定性因紊存在。应用集时分析联系数可以对其中的不确定性作定量描述和分析，从而提高学生成绩综合评定结果的客观性和合理性。     

基于熵率的密码芯片抵御SPA功耗攻击能力的量化方法

通过大量的工程实验获得了描述密码芯片功耗泄漏量随机性的两个关键指标:一是门级翻转数量的分布律,二是门级翻转数量的转移矩阵.以这两个关键指标为基础,引入信息论中熵率的概念,通过熵率的值动态地测量密码芯片在加密过程中功耗波形的熵值随机器周期数量的增长速度,进而有效地衡量密码芯片在SPA攻击下所具备的防御性能.     

Joint parameter estimation and decoding in a distributed receiver

This paper presents an algorithm for iterative joint channel parameter (carrier phase, Doppler shift, and Doppler rate) estimation and decoding of transmission over channels affected by Doppler shift and Doppler rate using a distributed receiver. This algorithm is derived by applying the sum-product algorithm (SPA) to a factor graph representing the joint a posteriori distribution of the information symbols and channel parameters given the channel output. In this paper, we present two methods for dealing with intractable messages of the SPA. In the first approach, we use particle filtering with sequential importance sampling for the estimation of the unknown parameters. We also propose a method for fine-tuning of particles for improved convergence. In the second approach, we approximate our model with a random walk phase model, followed by a phase tracking algorithm and polynomial regression algorithm to estimate the unknown parameters. We derive the Weighted Bayesian Cramer-Rao Bounds for joint carrier phase, Doppler shift, and Doppler rate estimation, which take into account the prior distribution of the estimation parameters and are accurate lower bounds for all considered signal-to-noise ratio values. Numerical results (of bit error rate and the mean-square error of parameter estimation) suggest that phase tracking with the random walk model slightly outperforms particle filtering. However, particle filtering has a lower computational cost than the random walk model-based method.     

支持个人移动的多代理系统网络协商思想

描述了支持个人移动,为用户提供智能接口以进行服务的多代理系统的结构和操作.本系统由下面的协议代理组成:个人通信代理（PCA）,给用户提供应用服务的智能接口;服务供应代理（SPA）,支持服务和用户间的通信;网络供应代理（NPA）,为SPA发出的请求提供网络连接.     

基于高光谱成像技术小麦籽粒霉变鉴别方法研究

小麦霉变籽粒是小麦不完善粒一种,鉴别小麦霉变粒是粮食霉变程度的重要参考。为了更精确地鉴别小麦霉变籽粒,本文利用高光谱成像技术采集不同品种小麦霉变籽粒及非霉变籽粒的光谱信息,建立小麦霉变籽粒的鉴别预测模型,实现小麦霉变籽粒快速、无损、有效、稳定的鉴别。首先收集了100粒霉变和100粒正常非霉变籽粒400-1000 nm范围的高光谱图谱,通过不同的光谱预处理方法进行处理,选出最优光谱信息预处理方法。接着,采用连续投影算法(SPA)和竞争性自适应重加权采样(CARS)提取特征波长,分别比较通过全波长范围和特征波长下建立的偏最小二乘判别分析(PLS-DA)和支持向量机(SVM)模型并进行比较。结果表明,淮麦22和宁麦13的最优预测模型分别为全波长-OSC-SVM和SPA-OSC-SVM模型,对应的R分别为0.9963和0.9998,RMSEP分别为0.0309和0.0064,R分别为0.9975和0.9995,RMSECV分别为0.0247和0.0111。     

Quantitative analysis of the content of nitrogen and sulfur in coal based on laserinduced breakdown spectroscopy: effects of variable selection

Coal is a crucial fossil energy in today's society,and the detection of sulfir(S) and nitrogen(N)in coal is essential for the evaluation of coal quality.Therefore,an efficient method is needed to quantitatively analyze N and S content in coal,to achieve the purpose of clean utilization of coal.This study applied laser-induced breakdown spectroscopy(LIBS) to test coal quality,and combined two variable selection algorithms,competitive adaptive reweighted sampling(CARS) and the successive projections algorithm(SPA),to establish the corresponding partial least square(PLS) model.The results of the experiment were as follows.The PLS modeled with the full spectrum of 27,620 variables has poor accuracy,the coefficient of determination of the test set(R~2 P) and root mean square error of the test set(RMSEP) of nitrogen were 0.5172 and 0.2263,respectively,and those of sulfur were0.5784 and 0.5811,respectively.The CARS-PLS screened 37 and 25 variables respectively in the detection of N and S elements,but the prediction ability of the model did not improve significantly.SPA-PLS finally screened 14 and 11 variables respectively through successive projections,and obtained the best prediction effect among the three methods.The R~2 P and RMSEP of nitrogen were0.9873 and 0.0208,respectively,and those of sulfur were 0.9451 and 0.2082,respectively.In general,the predictive results of the two elements increased by about 90% for RMSEP and 60% for R2 P compared with PLS.The results show that LIBS combined with SPA-PLS has good potential for detecting N and S content in coal,and is a very promising technology for industrial application.     

基于集对分析的P2P网络安全中的信誉度改进算法

P2P安全是P2P技术中的关键问题.传统基于信誉度的投票选举方法能够很好地反映P2P网络中未知节点的表现,为该节点的可信度提供可靠依据,但该方法并未将P2P网络中的不确定因素考虑进去.集对分析理论是一种研究不确定性问题的数学方法.本文提出了一种基于节点的不确定性的P2P网络信誉度安全机制,并采用集对分析方法对信誉度进行了定量分析.最后对两种算法做了对比分析,指出了改进算法的优越性.     

基于集对分析的综合评价方法及其应用

基于集对分析（SPA）的原理和方法，在介绍集对分析的思想和联系度有关概念后，提出评价系统各指标为连续型的等级综合评价方法，并用之对水稻高产性状和长江水质评价系统中，与相关文献的评价结果作对比，有一致的结论。从而验证方法的有效性。文中所用理论方法可推广应用于其他领域进行类似的评价。     

基于集对分析的模糊综合评判

集对分析是一种应用于方案决策的定性与定量相结合的方法。模糊综合评判是利用模糊集理论进行综合评价的一种方法。一般的模糊评判方法定性与定量结合时,如果量化细微,不仅增加计算工作量,而且也会与其模糊性相悖,导致评定结果可信度的降低;如果量化粗糙,亦会导致评定结果可信度的降低;模糊隶属函数的确定本身就是模糊数学理论在工程中应用的难点。结合集对分析方法和模糊综合方法对事物进行综合评判,能够真实反映研究对象的状况,具有很好的工程应用价值。