基于加权超图随机游走的文献关键词提取算法

针对科技文献类标题短文本关键词提取时,已有自然语言处理算法难以建模文献时间与权威性且短文本词语较少建模往往存在高维稀疏问题,本文提出了一个综合实时性以及权威性的关键词提取算法为研究者进行相关推荐.该方法将文献标题视为超边,将标题中不同词项视为超点来构建超图,并对超图中的超边与超点同时加权,进而设计一种基于加权超图随机游走的关键词提取算法对文献标题的词项进行提取.该模型通过对文献来源,发表年份以及被引次数建模来对超边进行加权,根据节点之间的关联度以及每对节点在特定标题中的共现距离对超点加权.最后,通过超图上的随机游走计算出节点的重要性进而确立可推荐的关键词.实验表明,与三种基准短文本关键词提取算法相比,本文算法在精确率和召回率方面均有所提高.     

基于改进CPD算法的SPECT-B超甲状腺图像配准

为了获得更多甲状腺肿瘤的诊断信息,文章提出了一种基于改进CPD算法的甲状腺肿瘤的SPECT图像和B超图像自动配准方法。首先,将参考图像(SPECT图像)和待配准图像(B超图像)分别通过阈值分割和图割的方法提取轮廓特征点;然后,用遗传算法和粒子群算法相结合的优化算法对CPD的权重参数进行自动寻优,利用改进的CPD算法对提取出的两组特征点进行匹配,得到两幅图像的空间变换参数;最后,将待配准图像按所求得的变换参数旋转、平移,从而获得配准后图像。实验结果表明,该方法能实现SPECT与B超甲状腺肿瘤图像的良好配准,具有参数少、精度高、鲁棒性好等特点。     

一种用于图像超分辨的实时高精度像素内配准方法

在超分辨图像复原处理中,像素内的配准精度、速度是超分辨图像最终实现的实时性和高质量的关键因素。传统的利用泰勒级数展开像素内配准方法实时性较差;分级少的块匹配配准精度相对较低。该文提出一种基于分段双三次多项式拟合的分级块匹配像素内配准技术,在算法复杂度低的同时保证了配准精度,并在文中给出了实验统计结果。     

改进BRISK特征的快速图像配准算法

为了实现超分辨率图像重建中高精度快速图像配准,提出一种改进BRISK特征的快速图像配准算法。原有BRISK算法在特征提取和匹配过程中,忽视了角点分布信息,其匹配策略单一,导致误匹配率高。针对该问题,首先利用BRISK算法构建连续尺度空间,在此基础上对图像进行分块,然后利用图像区域显著性自适应选择角点检测阈值,获得均匀分布的角点,最后利用快速最近邻FLANN算法结合RANSAC的方法进行二值特征快速匹配。实验结果表明:改进的BRISK算法相比原算法在保持速度的基础上达到亚像素级配准精度,并具有优越的场景适应性能。     

基于SLER检测的红外与可见光图像自动配准

针对可见光图像和红外图像配准问题,提出了一种新的自动配准方法.该算法通过同级极值区域检测子在灰度梯度图像上提取仿射协变区域.然后利用超图匹配算法确定匹配点对实现图像配准.该方法尤其适合于红外图像的质量或者边缘比对应的可见图像质量或边缘差情况下的异模配准.对一些具有挑战性的图像对进行试验,实验结果表明我们提出的方法比其他方法获得了更好的性能.     

基于PCA与聚类匹配的光谱图像二次配准

针对光谱图像配准方法效果较差的问题,提出一种基于PCA算法和聚类算法相结合新的特征点匹配算法并将二次配准方法引入到配准过程中。该方法首先提取SURF特征点并描述特征点,接着利用本文提出的特征点匹配算法对特征点进行匹配以完成初次配准,最后以初次配准结果作为初始值,采用改进的Powell算法利用图像灰度信息进行精配准。实验结果表明,该方法配准精度高,同时可以有效地缩短了光谱图像配准的时间。     

一种快速的亚像素图像配准算法

图像超分辨率重建是在现有红外探测器基础上提升空间分辨率的一种有效方法。超分辨率图像重建是利用一组相互之间存在亚像素位移的低分辨率图像构造出一幅高分辨率的图像,快速、高精度估计图像间的位移是其关键技术之一。提出了一种用于超分辨率重建的亚像素配准算法,算法由特征检测、像素级配准和亚像素级配准三个处理过程组成。在特征检测过程,首先采用梯度算子对图像进行边缘检测,然后对边缘点进行角点预检测,排除非角点像素点,之后再进行Harris角点检测,大大减少了计算量;在像素级配准过程,用NCC算法进行像素级配准,用统计方法去除误匹配点对;在亚像素级配准过程,先对像素级匹配点的邻域进行插值放大,再进行亚像素匹配,误匹配点剔除,相对偏移量计算。对提出的算法进行了仿真实验,结果显示本算法的速度较类似算法速度有较大的提高。     

连接向量特征匹配的暗场图像配准方法

利用损伤点之间的位置关系,根据光学元件损伤暗场图像的特点设计了一种基于连接向量特征匹配的配准方法。该方法首先对基准图像及待配准图像分别进行图像预处理,提取损伤点轮廓的中心坐标作为损伤点的位置值。然后构建损伤点连接向量,求出主方向并计算主方向下的连接向量特征,使用连接向量匹配获得匹配点对,最后利用RANSAC算法对匹配点对进行仿射变换参数计算。该方法具有旋转不变性,尺度不变性以及较高的配准准确度。实验对比分析了该方法与SIFT算法的计算效率及配准精度,结果表明在暗场图像条件下文中方法更有效且为背景单一,灰度信息较少同时要求较高的配准速度的场景下的图像配准问题提供了解决方案。     

基于梯度结构的星载红外图像和全色图像配准方法

针对红外图像与全色图像的不同的成像特性,提出了一种基于图像的梯度结构信息的匹配算法.首先对原始的红外和全色图像分别进行梯度计算,得到图像的梯度强度图;对梯度图进行结构相似性度量,获得图像间同名点对.然后采用RANSAC算法剔除误匹配的同名点.最后利用同名点对构建三角网小面元,并进行变换而得到配准图像.实验结果表明,算法可以有效地利用红外图像中地物的结构信息,匹配精度高.     

基于改进OS-SIFT的可见光与SAR图像自动配准

针对尺度不变特征变换（SIFT）算法配准可见光和合成孔径雷达（SAR）图像时性能较差的问题,提出了一种基于改进光学-SAR图像的SIFT(OS-SIFT)可见光和SAR图像配准算法。首先,利用非线性扩散滤波构建可见光和SAR图像的非线性扩散尺度空间,并采用多尺度Sobel算子和多尺度指数加权均值比算子分别计算可见光和SAR图像的一致性梯度信息。然后,用图像分块策略剔除尺度空间第一层后对尺度空间进行分块,在一致性梯度信息的基础上提取Harris特征点,得到稳定且均匀的点特征。基于梯度位置和方向直方图模板构建描述符并对其进行归一化处理,以克服影像间的非线性辐射差异。最后,利用欧氏距离进行特征匹配,并采用快速抽样一致性算法剔除误匹配。实验结果表明,相比联合位置、尺度和方向的SIFT算法和OS-SIFT算法,本算法的匹配率有明显提高,均方根误差也相对较低。     

可靠通信网多总线结构的超图设计法

本文在处理机数和可靠度给定情况下，先构造出成本最小、连通性最好图即核度最小图；将此图作为一类超图的代表图、救是其中阶数最小及端口数最小的超图的对偶图；最后根据对偶图，作出其对应的成本最小，可靠性最高的多总线结构。     

Correspondence Propagation with Weak Priors

For the problem of image registration, the top few reliable correspondences are often relatively easy to obtain, while the overall matching accuracy may fall drastically as the desired correspondence number increases. In this paper, we present an efficient feature matching algorithm to employ sparse reliable correspondence priors for piloting the feature matching process. First, the feature geometric relationship within individual image is encoded as a spatial graph, and the pairwise feature similarity is expressed as a bipartite similarity graph between two feature sets; then the geometric neighborhood of the pairwise assignment is represented by a categorical product graph, along which the reliable correspondences are propagated; and finally a closed-form solution for feature matching is deduced by ensuring the feature geometric coherency as well as pairwise feature agreements. Furthermore, our algorithm is naturally applicable for incorporating manual correspondence priors for semi-supervised feature matching. Extensive experiments on both toy examples and real-world applications demonstrate the superiority of our algorithm over the state-of-the-art feature matching techniques.      

On the capacity of uniform hypergraphs

The capacity of uniform hypergraphs can be defined as a natural generalization of the Shannon capacity of graphs. Corresponding to every uniform hypergraph there is a discrete memoryless channel in which the zero error capacity, in the case of the smallest list size for which it is positive, equals the capacity of the hypergraph, and vice versa. Also, the problem of perfect hashing can be considered as a hypergraph capacity problem. Upper bounds are derived for the capacity of uniform hypergraphs, using a technique developed earlier for perfect hashing based on the concepts of graph entropy and hypergraph entropy. These are subadditive functionals on probabilistic graphs and hypergraphs (i.e. graphs and hypergraphs within a probability distribution given on their vertex sets). A modified version of this technique is given, replacing graph entropy by another subadditive functional on probabilistic graphs. This functional can be considered as a probabilistic refinement of Lovasz's ∂-functional     

无线蜂窝网中基于Δ-邻域超图的信道重用模型

信道重用问题是基于频分多址技术的无线蜂窝网络中的一项关键技术,它关系到信道的传输效率,传统的方式是用冲突图模型来表示该问题。但是,由于冲突图模型中只考虑了两个小区之间的干扰,无法反映多个小区之间干扰的情况,又有人用超图模型来描述该问题。超图的建模为指数时间的,为了降低建模的计算复杂度,将该问题描述为Δ-邻域超图模型。性能分析结果表明,该模型既可以在多项式时间内完成建模,又可以充分反映多个小区之间的干扰关系。     

Further improve circuit partitioning using GBAW logic perturbation techniques

Efficient circuit partitioning is becoming more and more important as the size of modern circuits keeps increasing. Conventionally, circuit partitioning is solved without altering the circuit by modeling the circuit as a hypergraph for the ease of applying graph algorithms. However, there is room for further improvement on even optimal hypergraph partitioning results, if logic information can be applied for circuit perturbation. Such logic transformation based partitioning techniques are relatively less addressed. In this paper, we present a powerful multiway partitioning technique which applies efficient logic rewiring techniques for further improvement over already superior hypergraph partitioning results. The approach can integrate with any graph partitioner. We perform experiments on two-, three-, and four-way partitionings for MCNC benchmark circuits whose physical and logical information are both available. Our experimental results show that this partitioning approach is very powerful. For example, it can achieve a further 12.3% reduction in cut size upon already excellent pure graph partitioner (hMetis) results on two-way partitioning with an area penalty of only 0.34%. The outperforming results demonstrate the usefulness of this new partitioning technique.     

化简开关函数的图论方法

本文引入了n变量开关函数F(x1,,xn)的伴随图G和伴随超图H的概念,导出了下列方法和算法:(1)求F的所有本原蕴含项的图论方法和分支定界算法BBAPI;(2)应用超图理论求F的最小和表达式的算法AMSHT。这些方法简单、直观;既便于手算,也便于用计算机实现;计算效率高于常用的卡诺图法和Q-M列表法。     

基于压缩感知的线性调频信号频率估计

基于压缩感知理论,测量了在不重构情况下线性调频信号的频率。算法根据信号的稀疏表示建立原子库,利用AIC(Analog-to-Information Conversion)技术完成对信号的压缩采样,在压缩域利用正交匹配追踪的算法进而优化重构稀疏系数,寻找出系数最大值所在的位置,而原子库中该位置原子的频率参量即为线性调频信号的频率参量。该方法在保证频率估计高成功率的前提下,大大减少了采样过程中的冗余和浪费,节省了存储空间,实验仿真验证表明该方法的可行性。     

Hypergraph models for cellular mobile communication systems

Cellular systems have hitherto been modeled mostly by graphs for the purpose of channel assignment. However, hypergraph modeling of cellular systems offers a significant advantage over graph modeling in terms of the total traffic carried by the system. For example, we show that a 37-cell system when modeled by a hypergraph carries around 30% more traffic than when modeled by a graph. We study the performance of channelized cellular systems modeled by hypergraphs in comparison with those modeled by graphs. For this purpose, we have evaluated the capacities of these cellular networks defined in McEliece and Sivarajan (1994). Evaluation of the capacity necessitates generation of maximal independent sets of hypergraphs. We describe some new algorithms that we have developed for this purpose     

Crosspoint complexity of sparse crossbar concentrators

A sparse crossbar (n,m,c)-concentrator is a bipartite graph with n inputs and m outputs in which any c or fewer inputs can be matched with an equal number of outputs, where c is called its capacity. We present a number of new results on the crosspoint complexity of such concentrators. First, we describe a sparse crossbar (n, m, m)-concentrator whose crosspoint complexity matches Nakamura-Masson's (1982, 1977) lower bound for any given n and m. Second, we present a sparse crossbar (2m, m, m)-concentrator with crosspoint complexity also matching Nakamura-Masson's lower bound, and with fixed fan-in and nearly fixed fan-out. Third, we derive an easily computable lower bound on the crosspoint complexity of sparse crossbar (n, m, c)-concentrators. Finally, we show that this bound is attainable within a factor of two when n-m⩽c⩽[m/c]     

求网络总可靠度的状态空间树法和精确分解算法

本文提出了求通信网络总可靠度的状态空间树法。它直接产生网络图的一个不交化树多层多项式,优点是计算量较小[计算时间复杂度为0(?),(?)为边数,n_1为叶数],所得表达式较短。在此基础上应用超图理论提出了求通信网络总可靠度的精确分解算法。用它进行网络图的m次分解,一台计算机所能计算的通信网络规模可以扩大m倍。