Fast recursive algorithm for two-dimensional Tsallis entropy thresholding method

Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems. A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed. The key variables involved in calculating 2-D Tsallis entropy are written in recursive form. Thus, many repeating calculations are avoided and the computation complexity reduces to O(L2) from O(L4). The effectiveness of the proposed algorithm is illustrated by experimental results.     

改进的基于PSE和Tustin变换的分数阶系统求解递推算法

以分数阶算子近似方法的分析研究为基础,基于Tustin变换理论及其用于分数阶算子的离散生成函数公式特点,利用二项式幂函数的Maclaurin展开能够保证收敛的特性,考虑常用算法的局限性,提出了一种改进的基于幂级数展开和Tustin变换的分数阶运算方法,并应用于线性分数阶系统的求解,给出了递推算法的详细推导。算例仿真及其分析表明,该算法有效且具有良好的运算速度和精度。     

Efficient matrix inversion based on VLIW architecture

Matrix inversion is a critical part in communication, signal processing and electromagnetic system. A flexible and scalable very long instruction word （VLIW） processor with clustered architecture is proposed for matrix inversion. A global register file （RF） is used to connect al the clusters. Two nearby clusters share a local register file. The instruction sets are also designed for the VLIW processor. Experimental results show that the proposed VLIW architecture takes only 45 latency to invert a 4 × 4 matrix when running at 150 MHz. The proposed design is roughly five times faster than the DSP solution in processing speed.     

一种低信噪比下点目标检测新算法

针对红外探测系统对远距离目标进行实时临控的应用场合,提出了一种快速点目标检测算法。该算法将原始图像序列分割成多个小段,通过递推使用速度匹配滤波,能快速得到图像序列中目标轨迹的能量,从而提高低信噪比下点目标的检测能力。与其它检测算法相比,新算法具有检测概率高、算法复杂低等特点。对算法的原理和性能进行了详细地分析,通过仿真实验证明了该算法的有效性。     

宽度优先的频繁子图高效挖掘新算法

频繁子图已成为数据挖掘领域研究的热点之一。在经典的Apriori算法的基础上,提出了一种图挖掘的新算法Apriori-Graph。首先给出了一种新的、用于计算图的邻接矩阵规范编码的结点排序策略,大大降低了求图规范编码的复杂度,并可加速子图规范编码序列匹配的速度。其次,对候选子图的生成进行了规范。最后,针对频繁性检验这一瓶颈过程,给出了若干性质,从而较大地降低了候选子图频繁性判断的代价。实验结果表明,Apriori-Graph算法具有较高的挖掘效率。     

向量矩阵迭代自组织XML辅助聚类算法

为了提高海量XML文档集的聚类质量,提出了一种基于向量空间模型的矩阵迭代自组织XML辅助聚类算法。该算法以XML键为基础,把XML文档转化为向量矩阵,通过矩阵迭代自组织学习对XML文档实施取消、分裂与合并等优化措施。为了加速算法的收敛性,在算法中引入辅助策略,虽然不一定达到矩阵向量分类间隔最大化的目标,却在尽可能分类的情况下使得运算时间缩短,其XML键权重调整更有利聚类效果。对比其它向量聚类算法,一系列仿真实验表明所提出算法具有一定的有效性及合理性。     

多层前向神经网络带正则化因子的算法

针对权衰减递推最小二乘算法(trueweightdecayRLS,TWDRLS)每迭代一步计算复杂度和存储要求很大,基于局部线性最小二乘算法(locallinearizedleastsquaresalgorithm,LLLS)与正则化因子,给出了多层前向神经网络带正则化因子的LLLS算法,大大减小了TWDRLS算法每迭代一步计算的复杂度和存储量。实验表明,改进的算法提高了原LLLS算法的鲁棒性和泛化能力,其性能接近TWDRLS算法。     

基于双值设计结构矩阵的流程优化方法

DSM为系统设计提供了简单、精炼、可视化的表示的方法.业务流程的评价和优化与系统设计有相似之处.但由于业务流程涉及的参数更加复杂,因此原有的DSM不能直接应用于业务流程的优化.本文针对业务流程的特点,在设计结构矩阵（DSM）的基础上提出了基于双值设计结构矩阵（double value design structure matrix,DVDSM）算法,将DSM中的单值元素拓展为双值元素,扩展了元素所代表的信息量.文中以距离、路径值为例,设计了其详细的算法和规则及实现过程,并将算法应用于仓储物流管理系统的优化设计问题中.通过一系列仿真实验表明了算法的有效性.     

期望信号稳健阻塞的协方差矩阵重构波束形成算法

针对期望信号导向矢量存在失配时自适应波束形成器性能下降的问题,提出期望信号稳健阻塞的干扰噪声协方差矩阵重构算法。首先,构造角度展宽的信号阻塞矩阵,完成回波数据中期望信号的分离,进而利用无污染的回波数据计算准干扰噪声协方差矩阵。接着,对准干扰噪声协方差矩阵做特征分解,借助矩阵投影变换完成干扰噪声协方差矩阵的准确重构。最后,对剔除掉干扰和噪声分量的采样协方差矩阵做特征分解,完成期望信号导向矢量的有效估计。理论分析和仿真结果表明,所提算法不仅具有近乎理想的性能,还具有较低的计算复杂度。     

Nonnegative matrix factorization with Log Gabor wavelets for image representation and classification

1.INTRODUCTION Inpatternanalysisandcomputervision,visualrecog nitionofobjectsisoneofthemostchallengingprob lems.Approachestoovercomesuchproblemshavefo cusedonusingseveralmethodologies.Appearance basedrepresentationandrecognitionisoneofthe mostsuccessfullyusedtoday.Itinvolvespreprocess ingofmultidimensionalsignals,suchasimagesof facesandcharactersorspectrogramsofspeech.In fact,thecoreofthepreprocessingisthesocalleddi mensionalityreduction.Thedimensionalityreductionaimstocompress thehighdi…     

基于能力规划的三维概率选择矩阵优化算法

体系具有复杂性、巨大性和交互性等特征,体系需求的获取和分析则面临方案的不确定性和方案空间庞大等难题,利用启发式搜索算法可以求解规模较大的能力方案,但效率较低。在分析能力方案构成描述中定性、定量等要素特点的基础上,针对不同能力方案求解时算法执行效率差异较大的特征,提出面向智能Agent的三维概率选择矩阵算法,利用智能Agent自学习存储方式,将多种启发式优化算法求解不同类型的能力方案时的效率存储起来,建立三维选择矩阵,求解时动态选择效率高的算法,提高算法整体执行效率。在求解某体系能力规划方案时体现了此算法根据问题动态选择算法的优势。     

New UWB imaging algorithm for multiple targets detection

Because the conventional ultra wideband(UWB) radar imaging algorithm cannot meet the demand in the capability of multiple targets detection,a novel UWB radar imaging algorithm based on the near field radiation theory of dipole is presented.On the foundation of researching the principle of a time domain imaging algorithm,the back projection(BP) algorithm is derived and analyzed.Firstly,the far field sampling data are transferred to the near field sampling data by using the near field radiation theory of dipo...     

模糊互补判断矩阵排序的一种算法

对模糊一致性判断矩阵转换公式的参数进行了对比分析,给出了模糊互补判断矩阵排序的一个通用公式,并且把它推广到群体决策的情形,该公式不仅充分包含了模糊一致性判断矩阵的优良特性及其判断信息,而且所需计算量小、简洁、合理、有效,在实际应用中将给人们带来很大的方便,最后进行了算例分析。     

Diagonally loaded SMI algorithm based on inverse matrix recursion

The derivation of a diagonally loaded sample-matrix inversion (LSMI) algorithm on the busis of inverse matrix recursion (i.e.LSMI-IMR algorithm) is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.     

基于Hankel矩阵改进TLS-ESPRIT算法的散射中心参数提取及RCS重构

基于几何绕射理论(geometrical theory of diffraction,GTD)的散射中心信号模型可以精确描述隐身目标电磁散射特性,将总体最小二乘-旋转矢量不变技术(total least squares-estimating signal parameter via rotational in-vari...     

New analytical imaging algorithm for general case airborne bistatic SAR

This paper focuses on the general case （GC） airborne bistatic synthetic aperture radar （SAR） data processing, and a new analytical imaging algorithm based on the extended Loffeld＇s bistatic formula （ELBF） is proposed. According to the bistatic SAR geometry, the track decoupling formulas that convert the bistatic geometry to the receiver-referenced geometry in a concise way are derived firstly. Then phase terms of ELBF are decomposed into two independent phase terms as the range phase term and the azimuth phase term in a new way. To get the focusing result, the bistatic deformation （BD） term is compensated in the two-dimensional （2- D） frequency domain, and the space-variances of the range phase term and the azimuth phase term are eliminated by chirp scaling （CS） and chirp z-transform （CZT）, respectively. The effectiveness of the proposed algorithm is verified by the simulation results.     

基于粒子群优化的稀疏分解变尺度快速算法

针对一类可分稀疏性度量函数,结合最优化理论,研究了稀疏信号重构的快速算法。稀疏分解可以看成是一个带等式约束的优化问题,首先利用惩罚函数法将其转化为无约束优化问题|然后在粒子群优化估计搜索步长的基础上,利用变尺度法寻找无约束优化问题的最优解|最后依次增大惩罚因子,直至稀疏表示系数满足分解精度的要求。该算法避免了矩阵求逆运算,且无需先验地选取惩罚因子。仿真实验验证了算法的有效性和快速性。     

产品数据管理中任务指派问题的模型和算法

产品数据管理(product data management,PDM)中的任务具有紧前约束、可拆分特性和时间窗.为了使有限的设计资源得到合理利用,建立了产品数据管理中任务指派问题的数学模型,其目标是总项目工期最短,任务拆分次数最少和任务中断时间最短.设计了一种基于贪婪准则的遗传算法对模型进行求解,对遗传算法的染色体编码方案和解码规则,适值函数和遗传算子等进行了详细说明.最后给出了一个应用实例,验证了模型和算法的有效性.     

三维微波成像中基于对比源反演的扩展方法

采用基于非线性对比源反演算法的成像方法来重建放置在微波暗室内的三维电介质目标。在成像方法中采用正则化方法和频率跳变(frequency hopping, FH)方法等扩展手段。三维实测微波数据的实验设置是多频率、多收发分置的。三维实测微波数据的重建结果验证了基于对比源反演算法的扩展成像方法在三维微波成像中应用的可行性和精确性,是一种有应用前景的解决三维微波成像问题的处理方法。     

Degradation algorithm of compressive sensing

The compressive sensing(CS) theory allows people to obtain signal in the frequency much lower than the requested one of sampling theorem.Because the theory is based on the assumption of that the location of sparse values is unknown,it has many constraints in practical applications.In fact,in many cases such as image processing,the location of sparse values is knowable,and CS can degrade to a linear process.In order to take full advantage of the visual information of images,this paper proposes the concept of dimensionality reduction transform matrix and then selects sparse values by constructing an accuracy control matrix,so on this basis,a degradation algorithm is designed that the signal can be obtained by the measurements as many as sparse values and reconstructed through a linear process.In comparison with similar methods,the degradation algorithm is effective in reducing the number of sensors and improving operational efficiency.The algorithm is also used to achieve the CS process with the same amount of data as joint photographic exports group(JPEG) compression and acquires the same display effect.