Region-Based Hierarchical Image Matching

This paper presents an approach to region-based hierarchical image matching, where, given two images, the goal is to identify the largest part in image 1 and its match in image 2 having the maximum similarity measure defined in terms of geometric and photometric properties of regions (e.g., area, boundary shape, and color), as well as region topology (e.g., recursive embedding of regions). To this end, each image is represented by a tree of recursively embedded regions, obtained by a multiscale segmentation algorithm. This allows us to pose image matching as the tree matching problem. To overcome imaging noise, one-to-one, many-to-one, and many-to-many node correspondences are allowed. The trees are first augmented with new nodes generated by merging adjacent sibling nodes, which produces directed acyclic graphs (DAGs). Then, transitive closures of the DAGs are constructed, and the tree matching problem reformulated as finding a bijection between the two transitive closures on DAGs, while preserving the connectivity and ancestor-descendant relationships of the original trees. The proposed approach is validated on real images showing similar objects, captured under different types of noise, including differences in lighting conditions, scales, or viewpoints, amidst limited occlusion and clutter.     

基于遗传算法和模拟退火算法的TDOA定位技术

提出一种基于遗传算法与模拟退火算法的TDOA定位估计算法,该算法通过对求解定位坐标计算时的最大似然函数进行求解,实现了利用所有TDOA测量值对移动台的定位估计。该算法采用实数编码,自适应交叉率和变异率实现遗传算法的全局搜索,引入模拟退火的Boltzmann机制,解决遗传算法容易陷入局部最优的问题。实验结果表明,该算法定位精度高、收敛速度快。     

智能搜索算法求解最大团问题研究

最大团问题MCP（Maximum Clique Problem）在国外得到了广泛的研究,在国内刚起步,是一类NP完全问题。传统的确定性算法不能有效地进行求解。定义了MCP;介绍了使用启发式算法求解MCP的研究进展;综述了几种典型的智能搜索算法;分析了使用这些典型算法求解MCP的基本思想;研究了这些智能算法在求解MCP时的特点及性能。     

基于最大熵模型的中文名词短语识别

中文名词短语识别在自然语言处理已经得到了广泛应用。该文首先对名词短语识别问题进行描述,然后利用最大熵模型建立名词短语识别系统,通过实验选取最大熵模型的特征,最后利用选取的特征进行名词短语识别,实验结果表明系统达到了较高的准确率和召回率。     

汉语名物化复合词识别

名物化复合词的识别是汉语复合词识别中的难点.困难之处在于汉语动词和名词共现时既可以构成动词短语也可以构成名物化复合词.传统的汉语复合词识别往往只使用语料统计特征,效果往往不怎么理想.基于最大熵模型,在基准上下文特征的基础上,采用了词汇特征与Web特征对动词和名词共现时的名物化候选进行判定,取得了较好的实验结果.其中,Precision达到了86.31%,Recall达到了70.00%.     

核ICA在电流传感器相位差监测中的应用

介绍了核独立分量分析(ICA)的基本原理和算法,并将其用于对电流传感器输出的混合信号进行分离,通过比较分离出的单频测试信号输入前后的相位差,来标定传感器本身的相位差对其检测对象的影响。此外,还采用最大似然法对核ICA的分离效果进行评价。实验证明:在输入信号的信噪比为18.73dB的情况下,核ICA分离出的信号与源信号相位差在0.002 rad以内,达到了实际应用中所要求的误差范围。     

A hybrid clustering and graph based algorithm for tagSNP selection

TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm, to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has better performance than previous ones.     

Application of maximum entropy principle for reliability-based design optimization

The maximum entropy principle (MEP) is used to generate a natural probability distribution among the many possible that have the same moment conditions. The MEP can accommodate higher order moment information and therefore facilitate a higher quality PDF model. The performance of the MEP for PDF estimation is studied by using more than four moments. For the case with four moments, the results are compared with those by the Pearson system. It is observed that as accommodating higher order moment, the estimated PDF converges to the original one. A sensitivity analysis formulation of the failure probability based on the MEP is derived for reliability-based design optimization (RBDO) and the accuracy is compared with that by finite difference method (FDM). Two RBDO examples including a realistic three-dimensional wing design are solved by using the derived sensitivity formula and the MEP-based moment method. The results are compared with other methods such as TR-SQP, FAMM + Pearson system, FFMM + Pearson system in terms of accuracy and efficiency. It is also shown that an improvement in the accuracy by including more moment terms can increase numerical efficiency of optimization for the three-dimensional wing design. The moment method equipped with the MEP is found flexible and well adoptable for reliability analysis and design.     

A new scaling algorithm for the maximum mean cut problem

We present a new scaling algorithm for the maximum mean cut problem. The mean of a cut is defined by the cut capacity divided by the number of arcs crossing the cut. The algorithm uses an approximate binary search and solves the circulation feasibility problem with relaxed capacity bounds. The maximum mean cut problem has recently been studied as a dual analogue of the minimum mean cycle problem in the framework of the minimum cost flow problem by Ervolina and McCormick. A networkN=(G, lower, upper) with lower and upper arc capacities is said to be -feasible ifN has a feasible circulation when we relax the capacity bounds by ; that is, we use (lower(a)- , upper(a)+) bounds instead of (lower(a), upper(a)) bounds for each arca A. During an approximate binary search we maintain two bounds,LB andUB, such thatN is LB-infeasible andUB-feasible, and we reduce the interval size (LB, UB) by at least one-third at each iteration. For a graph withn vertices, m arcs, and integer capacities bounded byU, the running time of this algorithm is O(mn log(nU). This time bound is better than the time achieved by McCormick and Ervolina under thesimilarity condition (that is,U=O(n^o(1))). Our algorithm can be naturally used for the circulation feasibility problem, and thus provides a new scaling algorithm for the minimum cut problem.Research supported by a grant-in-aid of the Ministry of Education, Science and Culture of Japan.     

电力系统密集型频率信号的测量与分析

针对非同步采样条件下密集频率信号无法准确测量的问题,提出一种密集型频率信号检测方法。基于离散傅里叶变换建立密集型频率信号模型,然后对单通道观测信号做周期延拓,形成多路信号。使用可变主成分分析法进行去相关性处理。再基于极大似然盲源分离法求解密集型频率信号模型。最后根据比例系数校正各频率成分参数。仿真和实验结果表明,所提方法具有较高的精度和一定的抗噪声能力。