Q的线性密码分析

对NESSIE公布的17个分组密码之一的Q进行了线性密码分析，攻击所需的数据复杂不大于2^118(相应的成功率为0．785），空间复杂度不大于2^33 2^19 2^18 2^12 2^11 2^10。此结果显示Q对线性密码分析是不免疫的。     

归一双向加权(2D)2PCA的手指静脉识别方法

为快速有效地进行手指静脉识别,针对双向二维主成分分析算法降维的特点,并对该算法进行改进,提出在经过图像预处理的手指静脉图像基础上,特征值归一化并双向加权(2D)2PCA的手指静脉识别方法((OW2D)2PCA)．分析了累积特征率对(2D)2PCA的影响,以及加权值、特征值归一加权值和累积特征率对W(2D)2PCA、OW(2D)2PCA、(W2D)2PCA、(OW2D)2PCA的影响．通过建立手指静脉图像库的实验结果表明,文中提出方法能够取得较好的识别效果;对(2D)2PCA提取特征向量中的冗余信息有很强的抑制作用,双向加权比单向加权效果更好;而且(OW2D)2PCA的平均识别率高于2DPCA、(2D)2PCA、W(2D)2PCA、(W2D)2PCA和OW(2D)2PCA．     

F2+uF2和Z4上循环码的Gray象

利用Gray映射Φ的性质,研究了环F₂+uF₂和Z₄上的任意长循环码。证明了环F₂+uF₂上任意长码是循环码当且仅当它的Gray象是域F2上的准循环码,得到了Z₄上任意长码是循环码的一个充分必要条件。特别的,环F₂+uF₂上长为n的线性循环码的Gray象是域F₂上指标为2长为2n的线性准循环码,环Z₄上长为n的线性循环码的Gray象是域F₂上指标为2长为2n的准循环码。     

一种等价于PI的二型模糊控制器设计算法

区间二型模糊集合将次隶属度做了简化,基于KM降阶算法的区间二型模糊控制器实现起来相对简单.虽然区间二型模糊控制器在一定程度上优于传统的一型模糊控制器或者PI控制器等,但区间二型模糊控制器并没有充分利用二型模糊集合的次隶属度信息.为解决这些问题,研究了普通二型模糊控制器的一般结构,提出了一种等价于PI的二型模糊控制器.该...     

157百合（Lilium cr.Gran sasso）染色体核型研究

本文对１５７百合进行了染色体核型研究,结果表明：１５７百合体细胞染色体数为２ｎ＝２ｘ＝２４;染色组成为Ｒ（２ｎ）＝２ｘ＝２ｍ（ＳＡＴ）＋２ｍ＋２Ｓｍ（ＳＡＴ）＋１６Ｓｔ＋２ｔ;在第１,２,对染色体上有随体;其核型分类属于３Ｂ型。     

基于对等网的流媒体数据分配算法

提出一种基于对等网的流媒体数据分配算法(DA2SMp2p),可根据网络环境的变化动态调整数据分配,在提供节点中途失效时,可以比MBDAp2p算法、OTSp2p算法和Algorithm_1算法保持更好的流媒体连续性,提供节点没有失效时,所取得的段缓冲延迟与MBDAp2p算法相同,比OTSp2p算法和Algorithm_1算法小。DA2SMp2p算法、MBDAp2p算法和OTSp2p算法保持连续播放的最小缓冲延迟相同,都比Algorithm_1算法小。     

完全对称的P2P技术在高校远程教育中的应用研究

为了让P2P技术能够在高校远程教育中等到更好的应用,提出了完全对称结构的P2P体系结构.通过大量的调查研究,分析了传统的主从结构的P2P体系结构存在的问题,包括性能上的瓶颈和管理上的局限性.在此基础上,提出了完全对称结构的P2P体系结构,并设计和构建主从结构的P2P体系结构和完全对称结构的P2P体系结构算法模型.在建立算法模型后,进行了大量的模拟测试.通过效果对比,验证了完全对称的P2P体系结构不仅进一步提高资源搜索效率和数据传输效率,还能大幅度提高整个系统的高可用性,更重要是能让远程教育系统的处理能力进行线性扩展.     

Structural two-dimensional principal component analysis for image recognition

In this paper, a new technique called structural two-dimensional principal component analysis (S2DPCA) is proposed for image recognition. S2DPCA is a subspace learning method that identifies the structural information for discrimination. Different from conventional two-dimensional principal component analysis (2DPCA) that only reflects within-row information of images, the goal of S2DPCA is to discover structural discriminative information contained in both within-row and between-row of the images. By contrast with 2DPCA, S2DPCA is directly based on the augmented images encoding corresponding row membership, and the projection directions of S2DPCA are obtained by solving an eigenvalue problem of the augmented image covariance matrix. Computationally, S2DPCA is straightforward and comparative with 2DPCA. Like 2DPCA, the singularity problem is completely avoided in S2DPCA. Experiments on face recognition and handwritten digit recognition are presented to show the effectiveness of the proposed approach.     

ZrO_2-Y_2O_3-Al_2O_3电解质性能研究

为了改善ZrO2-Y2O3电解质性能,在ZrO2-Y2O3材料中加入Al2O3形成ZrO2-Y2O3-Al2O3新材料,结果表明:ZrO2-Y2O3-Al2O3材料的力学及抗热震性能得到明显改善,离子电导率也得到了提高。     

Ag掺杂SnO2纳米纤维的制备及其气敏特性研究

以聚乙烯醇(PVA)和SnCl2·2H2O为原料采用静电纺丝技术制备纯sno2及Ag掺杂sno2纳米纤维.经700℃退火烧结后制得了连续多孔的snO2纳米纤维.研究了Ag的掺杂对SnO2纳米纤维的C2H2气体敏感性能的影响,结果表明Ag的掺杂对SnO2纳米纤维的C2H2气体敏感性能具有明显的影响,在Ag掺杂量为8at%...     

SnO_2/SiO_2双层薄膜的湿敏特性

本实验是在单晶硅片上热生长一层ＳｉＯ２，然后用真空淀积的方法获得一层超微粒ＳｎＯ２薄膜，通过对ＳｎＯ２／ＳｉＯ２薄膜电阻与相对湿度关系的测试，发现阻湿的线性特性和灵敏度明显优于ＳｎＯ２薄膜和ＳｉＯ２薄膜，测湿范围明显展宽。     

A Type-2 Self-Organizing Neural Fuzzy System and Its FPGA Implementation

This paper proposes a type-2 self-organizing neural fuzzy system (T2SONFS) and its hardware implementation. The antecedent parts in each T2SONFS fuzzy rule are interval type-2 fuzzy sets, and the consequent part is of Mamdani type. Using interval type-2 fuzzy sets in T2SONFS enables it to be more robust than type-1 fuzzy systems. T2SONFS learning consists of structure and parameter identification. For structure identification, an online clustering algorithm is proposed to generate rules automatically and flexibly distribute them in the input space. For parameter identification, a rule-ordered Kalman filter algorithm is proposed to tune the consequent-part parameters. The learned T2SONFS is hardware implemented, and implementation techniques are proposed to simplify the complex computation process of a type-2 fuzzy system. The T2SONFS is applied to nonlinear system identification and truck backing control problems with clean and noisy training data. Comparisons between type-1 and type-2 neural fuzzy systems verify the learning ability and robustness of the T2SONFS. The learned T2SONFS is hardware implemented in a field-programmable gate array chip to verify functionality of the designed circuits.      

二维非对称受限编码信道容量的证明

为了判断二维非对称受限编码的信道容量是否为正,提出了扫描方法.若满足限制(d1,k1,d2,k2)矩阵中的每个位置都可以通过已知的标志来决定并且被扫描,则限制(d1,k1,d2,k2)的信道容量为0.通过对特定二维受限编码信道容量的证明,验证了扫描方法比代数与组合方法更为有效.同时采用证明信道容量大于零常用的技术,找到满足(d1,k1,d2,k2)受限的两个m×n矩阵,若两矩阵在各种变形下都满足(d1,k1,d2,k2)限制,则信道容量Cd1,k1,d2,k2≥1/mn.这一方法对信道容量为正的区域进行扩展.     

基于双向压缩二维保局投影的人脸识别方法

二维保局投影(2DLPP)只在图像的横向进行数据压缩,提取的特征维数较高,针对该问题,结合二维保局投影和可选的二维保局投影,提出双向压缩二维保局投影((2D)2LPP)算法。该算法从横向和纵向2个方向实施2DLPP,使图像的横向和纵向的维数都得到有效的约简。实验结果表明,(2D)2LPP在识别率和识别时间上都优于2DLPP和A2DLPP。     

改进的低功耗两步式ADC结构

本文提出了一种改进的两步式ADC拓扑结构。当ADC的分辨率为n位时,这种结构只需要(2~(n/2+1-2))或(2~(n-1)/2+2~(n+1/2)-2)个比较器。与传统的两步式ADC相比,其比较器数目的大大减少,使得ADC电路的功耗和芯片面积随之显著降低。此结构适用于高速便携式VLSI系统。     

基于数据库编程语言的海量邮件数据分类技术

针对海量邮件数据的处理需求和实际业务需要,设计了基于数据库编程语言的海量邮件自动分类系统。该系统由特征学习模块、数据库查询模块和贝叶斯分类模块3部分构成。结合贝叶斯分类算法,利用PL/SQL语言与数据库交互时的高效性特点,在ORACLE PL/SQL存储过程中完成对未知邮件的特征提取和表示,实现对海量邮件数据的有效分类。     

模块2DPCA的缺陷与改进

模块2DPCA是2DPCA的推广,在识别性能上比2DPCA更具鲁棒性。本文分析了模块2DPCA在计算训练样本总体散布矩阵和本征向量选取方面的缺陷,提出了一种改进的模块2DPCA算法。实验结果表明,改进后的算法能更好地选取本征向量,更有效地提取人脸特征。     

Type-2 hierarchical fuzzy system for high-dimensional data-based modeling with uncertainties

A type-2 hierarchical fuzzy system (T2HFS) is presented for the high-dimensional data-based modeling with uncertainties. Type-2 fuzzy logic system (T2FLS) is a powerful tool to handle uncertainties in complex processes. However, the operation of type-reduction has greatly increased the computational burden of T2FLSs. By integrating the T2FLS with hierarchical structure, a systematic design methodology of T2HFS is proposed to avoid the rule explosion and to simplify the computation complexity. The design methodology has included several procedures to establish the T2HFS. Firstly, the PCA-based method is developed to capture the prominent component from training data, and to determine the hierarchical structure of T2HFS. Furthermore, a novel clustering method is proposed to design the basic type-2 fuzzy logic unit (T2FLU) in uncertain environments. Finally, a hybrid-learning method is presented to fine-tune the parameters for the global optimization where the statistical and deterministic optimization methods are developed for the nominal and auxiliary performance, respectively. Simulation results have shown that the proposed T2HFS is very effective for the high-dimensional data-based modeling and control in uncertain environment.     

基于FPSO的电力巡检机器人的广义二型模糊逻辑控制

针对电力巡检机器人(Power-line inspection robot, PLIR)的平衡调节问题, 设计了广义二型模糊逻辑控制器(General type-2 fuzzy logic controller, GT2FLC); 针对GT2FLC中隶属函数参数难以确定的问题, 通过模糊粒子群(Fuzzy particle swarm optimization, FPSO)算法来优化隶属函数参数. 将GT2FLC的控制性能与区间二型模糊逻辑控制器(Interval type-2 fuzzy logic controller, IT2FLC)和一型模糊逻辑控制器(Type-1 fuzzy logic controller, T1FLC) 的控制性能进行对比. 除此之外, 还考虑了外部干扰对三种控制器控制效果的影响. 仿真结果表明, GT2FLC具有更好的性能和处理不确定性的能力.     

Time- and Space-optimal height-balanced 2-3 brother trees

The node-visit optimal (NVO) and the space-cost optimal (SCO) height-balanced (HB) 2-3 brother trees are defined. The characterization of the NVO HB 2-3 brother trees is developed. This characterization leads to a linear-time algorithm for constructing an NVO HB 2-3 brother tree for an ordered set of keys. The minimum space-cost of an N-key NVO HB2-3 brother tree and the space-cost of an N-key SCO HB 2-3 brother tree is analysed. It is shown that the minimum space-cost of an NVO HB 2-3 brother tree is never more than one plus the space-cost of an SCO HB 2-3 brother tree. Further, the minimum node-visit cost of an SCO HB 2-3 brother tree is at most one plus the node-visit cost of an NVO HB 2-3 brother tree. It is also shown that there exists an HB 2-3 brother tree which is both SCO and NVO for just over half the possible values of keys. Finally, an outline for constructing an SCO HB 2-3 brother tree is presented.