一种改进的多目标决策指标权重计算方法

在多目标决策中,通常都涉及到指标权重的计算问题．针对现有权重计算方法中存在的不足,提出了一种改进的熵权层次分析法．该方法将熵权法和层次分析法的中间过程相结合,将熵权法的底层指标客观权重与层次分析法的子准则主观权重对应结合后,再与上层指标权重综合,归一化后得到最终的指标权重．结果表明,求得的权重具有更高的可信度．     

组网无源雷达变数目多目标跟踪算法

针对组网无源雷达多目标跟踪问题,提出一种新的变数目多目标跟踪算法,实时估计目标数目与多目标状态．算法采用多站集中式融合策略解决无源观测的不完全性问题,采用最小二乘算法构造伪位置观测解决无源观测的非线性问题．针对变数目多目标跟踪问题,利用随机集理论将多目标状态与观测构成随机有限集,通过高斯混合概率假设密度滤波递归计算多目标状态随机有限集的后验强度,实时得到目标数目及其状态的估计．算法引进最小二乘算法估计出候选目标点进行数据关联,解决了无源观测线较近时无源数据关联精度下降问题．仿真实验验证了该算法的有效性．     

采用粒子滤波和模糊聚类法的非线性多目标跟踪

提出一种新的非线性多目标跟踪方法,用模糊聚类算法实现数据关联,采用粒子滤波实现对各目标的独立跟踪．首先利用最大熵模糊聚类对目标和观测数据进行关联,采用模糊隶属度重建多目标滤波中的联合关联概率矩阵．然后利用粒子滤波适于处理非线性问题的特点,通过联合关联信息,采用粒子滤波独立对各目标进行滤波,实现对目标状态的更新．最后,将该算法应用于多传感器多目标纯方位角跟踪．仿真结果表明,相比于联合概率数据关联算法及MEF-JPDAF,新算法具有更高的跟踪精度．     

基于统计学习的自适应文本聚类

针对文本数据的高维性和稀疏性从而使传统的聚类算法在文本聚类应用中的表现不能让人满意的问题,通过计算文档相似度矩阵,在聚类过程中动态地统计学习已划分和未划分文本集合的相关信息,探测剩余未划分的数据集中的与已划分类簇覆盖度较小的最大密集区域,逐步生成预定数目的初始聚类中心集合,最后将剩余文档划分到最相似的初始聚类中心集合完成聚类,从而有效地减小了划分聚类算法对初始聚类中心的敏感性。算法中的一些阈值参数均通过在聚类过程中动态地对数据集进行统计学习得到,避免了多数聚类算法通过经验或实验设定阈值参数的盲目性,在不同     

一种TDD-MIMO系统混合预编码传输机制

针对TDD-MIMO系统中,天线之间存在相关性时会影响系统性能的问题,提出一种混合预编码传输机制.在该机制中,基站首先采用一种低复杂度的信道估计算法来计算信道矩阵,然后计算信道矩阵的相关度来判断相关性的高低并选择相应的预编码方式.当相关度大于等于转换系数时,采用基于协方差矩阵的预编码;反之,则利用基于LR的预编码.仿真结果表明,该机制充分利用了2种预编码分别适用于不同相关性范围的特点,在降低了系统的误码率的同时保持了低复杂度,提高了系统在天线之间存在相关性时的容量.仿真验证了该机制的有效性.     

Effects of deep etching methods on the microstructure of the etched vias of the silicon-based SIWF

The microstructure and the array accuracy of the etched vias of the silicon-basedsubstrate integrated waveguide filter (SIWF) are crucial to the electromagnetic performance and the reliability of the silicon-based SIWF. In this paper, three different etching methods, including potassiumhydroxide etching, picosecond UV laser etching, and inductively coupled plasma (ICP) etching are utilized to etch via arrays onhigh resistivity ［100］-siliconsubstrates. The profiles and the array accuracy of the vias are measured by optical critical dimension and the micromorphology of the vias is characterized byscanning electron microscopy (SEM), on the basis of which the effects of different deep etching methods on the microstructure of the viasidewall of the silicon-based SIWF are studied. The results indicate that the microstructure of the vias etched by the inductively coupled plasma etching method is the best. Meanwhile, this kind of vias has the highest array accuracy and the lowest roughness. So, under the current condition of process equipment and technical level, ICP etching is the optimal method for manufacturing deep via arrays of the silicon-based SIWF.     

Wonderful events automatic detection and location of the HCRF and webcast text

Based on the powerful function of the hidden conditional random fields (HCRF) model in the expression and identification of semantic events and combining the webcast text information, a new framework for wonderful events automatic detection is put forward. Firstly, by analyzing and processing the webcast text, keyword combinations corresponding to each exciting event are obtained. Secondly, by classifying the webcast text to be detected, the happening time labels of each wonderful event are obtained. Thirdly, an HCRF model for semantic shot annotation is built to realize the semantic annotation of multiple types of semantic shots simultaneously, and the semantic shot sequence of the video clip is obtained. Finally, combining the multi-modal semantic clues, an HCRF model for the wonderful events detection and localization is effectively built in the case of small-scale training samples. Based on the mapping relationship among video low-level features, the multi-modal semantic clues and the wonderful semantic events, the inherent patterns of the wonderful events are excavated deeply in the multiple dimensions of the semantic structure, and then the wonderful events automatic detection, localization and segmentation are precisely achieved. Experiments show the effectiveness of this model.     

Low complexity quantum private queries protocol

Private information retrieval(PIR) is an important privacy protection issue of secure multi-party computation, but the PIR protocols based on classical cryptography are vulnerable because of new technologies,such as quantum computing and cloud computing. The quantum private queries(QPQ) protocols available, however, has a high complexity and is inefficient in the face of large database. This paper, based on the QKD technology which is mature now, proposes a novel QPQ protocol utilizing the key dilution and auxiliary parameter. Only N quits are required to be sent in the quantum channel to generate the raw key, then the straight k bits in the raw key are added bitwise to dilute the raw key, and a final key is consequently obtained to encrypt the database. By flexible adjusting of auxiliary parameters θ and k, privacy is secured and the query success ratio is improved. Feasibility and performance analyses indicate that the protocol has a high success ratio in first-trial query and is easy to implement, and that the communication complexity of O(N) is achieved.     

ID-based trapdoor mercurial commitment under one-way functions assumptions

The notion of identity-based trapdoor mercurial commitment incorporates the advantages of both identity-based trapdoor commitment and trapdoor mercurial commitment. So far, the existing identity-based trapdoor mercurial commitment schemes are based on the strong Diffie-Hellman assumption or computational Diffie-Hellman assumption. One-way function existence is one of the fundamental assumptions in the cryptography. In this paper, we first propose a general construction for identity-based trapdoor mercurial commitment based on the one-way function. Meanwhile, we give a concrete instantiation based on the Boneh-Boyen signature scheme.     

Unsupervised SAR image segmentation using TMF and belief propagation

To solve the problem that the traditional statistical inference approach for the triplet Markov fields (TMF) model cannot balance segmentation accuracy and computational efficiency, an efficient statistical inference approach for the TMF model using belief propagation is proposed, and then applied to unsupervised synthetic aperture radar (SAR) image segmentation. The algorithm combines the TMF model and the statistical property of the SAR image, and translates the segmentation problem into maximization of the posterior marginal (MPM) estimation. For the two label fields in TMF, the belief propagation algorithm is generalized to the bivariate case to estimate the joint posterior marginal probability of the two label fields through message passing. The two label fields can be simultaneously estimated according to the MPM criterion. Experiments on both simulated and real SAR images demonstrate that the proposed algorithm can efficiently suppress the influence of the speckle, and obtain accurate segmentation results with a reasonable computational cost.