Improving path planning efficiency for underwater gravity-aided navigation based on a new depth sorting fast search algorithm

This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.

基于改进FAST的电力工程图纸识别与校核技术

针对人工评审电力施工图预算工程量过程中存在的耗时费力及准确性较低等问题,设计了一种基于改进FAST算法与VGG网络的工程图纸识别与数据校核模型。该模型针对传统FAST算法误判率高、抗噪声性能差等不足,提出了基于积分核的改进FAST算法,以降低角点检测误判率和检测时间。并采用VGG网络进行输入特征与图纸数据校核之间的关联分析,从而实现了电力工程图纸符号智能识别与电力工程量的智能校核。算例验证结果表明,所提IFAST-VGG算法对图纸识别与工程量校核的平均准确率分别为90.6%和91.6%,均高于其他对比算法,可以应用于实际工程中。

基于数据驱动的FAST主动反射面调节优化模型

针对500 m口径球面射电望远镜(five-hundred-meter aperture spherical radio telescope,FAST)的主动反射面调节问题,利用旋转抛物面在三维空间中的定义建立了一个对任意天体角度均适用的工作抛物面方程,该方法不同于以往的坐标旋转的方法。利用反射面板重心点作为反射点,将反射接收比定义为能把光线反射到馈源舱被其接收的面板数量与300 m口径工作抛物面下总面板数量的比值。结合主索节点径向伸缩距离、边界平稳过度和邻接距离变化幅度三个约束条件,以接收比最大化作为目标函数,建立了一个工作抛物面优化模型,并利用节点数据和模拟退火算法对其进行求解,得到了工作理想抛物面。选用两组天体角度进行实例分析,结果显示调节后的接收比增大12.82%,并给出了工作主索节点的部分径向调节方案。本研究为FAST对于任意天体角度的变形提供了一种新的建模方法,也对馈源舱反射接收比提出了一种新的计算方式。

A novel fast classification filtering algorithm for LiDAR point clouds based on small grid density clustering

Clustering filtering is usually a practical method for light detection and ranging(LiDAR)point clouds filtering according to their characteristic attributes.However,the amount of point cloud data is extremely large in practice,making it impossible to cluster point clouds data directly,and the filtering error is also too large.Moreover,many existing filtering algorithms have poor classification results in discontinuous terrain.This article proposes a new fast classification filtering algorithm based on density clustering,which can solve the problem of point clouds classification in discontinuous terrain.Based on the spatial density of LiDAR point clouds,also the features of the ground object point clouds and the terrain point clouds,the point clouds are clustered firstly by their elevations,and then the plane point clouds are selected.Thus the number of samples and feature dimensions of data are reduced.Using the DBSCAN clustering filtering method,the original point clouds are finally divided into noise point clouds,ground object point clouds,and terrain point clouds.The experiment uses 15 sets of data samples provided by the International Society for Photogrammetry and Remote Sensing(ISPRS),and the results of the proposed algorithm are compared with the other eight classical filtering algorithms.Quantitative and qualitative analysis shows that the proposed algorithm has good applicability in urban areas and rural areas,and is significantly better than other classic filtering algorithms in discontinuous terrain,with a total error of about 10%.The results show that the proposed method is feasible and can be used in different terrains.

Improvement and performance of parallel multilevel fast multipole algorithm

The method of establishing data structures plays an important role in the efficiency of parallel multilevel fast multipole algorithm(PMLFMA).Considering the main complements of multilevel fast multipole algorithm(MLFMA) memory,a new parallelization strategy and a modified data octree construction scheme are proposed to further reduce communication in order to improve parallel efficiency.For far interaction,a new scheme called dynamic memory allocation is developed.To analyze the workload balancing performance of a parallel implementation,the original concept of workload balancing factor is introduced and verified by numerical examples.Numerical results show that the above measures improve the parallel efficiency and are suitable for the analysis of electrical large-scale scattering objects.

An adaptive reanalysis method for genetic algorithm with application to fast truss optimization

尽管为结构的优化的基因算法(GA ) 是很柔韧的，它比 optimality 标准和数学编程方法很计算地集中、因此慢。加快设计过程，在场的作者为 GA 的一个适应分析方法和它在最佳的设计的应用捆绑。这种分析技术首先从樱桃酒鈥檚 被导出联合近似方法。一个重复计划被采用适应地在每代决定基础向量的数字。以便说明这个方法，三个古典例子最佳捆绑设计被用来验证建议基于 reanalysis 的设计过程。介绍数字结果证明适应分析技术很稍微影响最佳的解决方案的精确性并且确实加速设计进程，特别为大规模结构。关键词捆绑结构 - 适应分析 - 基因算法 - 快优化工程被中国(50975121 ) 和吉林的毕业生革新资金的工程 2009-2007 的国家自然科学基金会支持大学。

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(L^2)from O(L^4).The effectiveness of the proposed algorithm is illustrated by experimental results.

General and efficient parallel approach of finite element-boundary integral-multilevel fast multipole algorithm

A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finite-element-boundary-integral-multi-level fast multipole algorithm (FE-BI-MLFMA). Among many algorithms of FE-BI-MLFMA, the decomposition algorithm (DA) is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization. On the basis of the DA, the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finite-element method and the parallelized MLFMA for the matrix from the boundary integral method respectively. The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor-mance computing platform CEMS-Liuhui. Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy, efficiency, and generality.

Image Reconstruction from Fan-Beam Projections without Back-Projection Weight in a 2-D Dynamic CT: Compensation of Time-Dependent Rotational, Uniform Scaling and Translational Deformations

In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.

Efficient analysis of dielectric radomes using multilevel fast multipole algorithm with CRWG basis

A full-wave analysis of the electromagnetic problem of a three-dimensional (3-D) antenna radiating through a 3-D dielectric radome is preserued. The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW) approach for homogeneous dielectric objects and the electric field integral equation for conducting objects. The integral equations are discretized by the method of moment (MoM), in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions. The resultant matrix equation is then solved by the multilevel fast multipole algorithm (MLFMA) and fast far-field approximation (FAFFA) is used to further accelerate the computation. The radiation patterns of dipole arrays in the presence of radomes are presented. The numerical results demonstrate the accuracy and versatility of this method.

Fast Algorithm for Nonsubsampled Contourlet Transform

多尺度的几何分析(MGA ) 为图象处理作为有效策略被认出了。作为 MGA 的分离工具之一， nonsubsampled contourlet 变换(NSCT ) 广泛地被使用了图象降噪，图象熔化，图象改进，特征抽取等等。然而，处理表演由于它的高冗余性被限制，并且导致集中的计算效率。因此，它的快算法在实践被需要。在这份报纸，我们采用一个优化方向性的过滤器银行(DFB ) 并且把它嵌进 NSCT 当使重建的表演的损失细微时，显著地加速计算速度。试验性的结果证明重建的图象质量能满足人的视觉系统。而且，改进 NSCT 有速度关于若干次比传统的的。图象降噪上的试验性的结果也验证建议方法的可行性和效率。

A novel adjustable multiple cross-hexagonal search algorithm for fast block motion estimation

In this paper,we propose a novel adjustable multiple cross-hexagonal search(AMCHS) algorithm for fast block motion estimation. It employs adjustable multiple cross search patterns(AMCSP) in the first step and then uses half-way-skip and half-way-stop technique to determine whether to employ two hexagonal search patterns(HSPs) subsequently. The AMCSP can be used to find small motion vectors efficiently while the HSPs can be used to find large ones accurately to ensure prediction quality. Simulation results showed that our proposed AMCHS achieves faster search speed,and provides better distortion performance than other popular fast search algorithms,such as CDS and CDHS.

A RECURSIVE AND PARALLEL FAST JPDA ALGORITHM

Joint Probabilistic Data Association (JPDA) is a very fine optimal multitarget tracking and association algorithm in clutter. However, the calculation explosion effect in computation of association probabilities has been a difficulty. This paper will discuss a method based on layered searching construction of association hypothesis events. According to the method, the searching schedule of the association events between two layers can be recursive and with independence, so it can also be implemented in parallel structure. Comparative analysis of the method with relative methods in other references and corresponding computer simulation tests and results are also given in the paper.

A FAST ALGORITHM FOR DISCRETE HARTLEY TRANSFORM OF ARBITRARY LENGTH

DHT of length plq（p is odd and q is arbitrary） is turned into pl DHTs of length qand some additional operations, while the additional operations only involves the computation ofcos-DFT and sin-DFT with length p. If the length of a DHT is p1l1…PNlN2l（P1…,PN are oddprimes）, a fast algorithm is obtained by the similar recursive technique. Therefore, the algorithmcan compute DHT of arbitrary length. The paper also Proves that operations for computingDHT of length N by the algorithm are no more than O（Nlog2N）, when the length is N=pl,operations of the algorithm are fewer than that of other known algorithms.

NEW FAST ALGORITHM OF 2-D DISCRETE COSINE TRANSFORM

In this paper, a new algorithm for the fast computation of a 2-D discrete cosine transform (DCT) is presented. It is shown that the N×N DCT, where N = 2m, can be computed using only N 1-D DCT’s and additions, instead of using 2N 1-D DCT’s as in the conventional row-column approach. Hence the total number of multiplications for the proposed algorithm is only half of that required for the row-column approach, and is also less than that of most of other fast algorithms, while the number of additions is almost comparable to that of others.

Fast direction of arrival algorithm based on vector-sensor arrays using wideband sources

An acoustic vector sensor(AVS)can capture more information than a conventional acoustic pressure sensor(APS).As a result,more output channels are required when multiple AVS are formed into arrays,making processing the data stream computationally intense.This paper proposes a new algorithm based on the propagator method for wideband coherent sources that eliminates eigen-decomposition in order to reduce the computational burden.Data from simulations and lake trials showed that the new algorithm is valid:it resolves coherent sources,breaks left/right ambiguity,and allows inter element spacing to exceed a half-wavelength.

A Fast Algorithm to Solve the Bitsadze Equation in the Unit Disk

An algorithm is provided for the fast and accurate computation of the solution of the Bitsadze equation in the complex plane in the interior of the unit disk. The algorithm is based on the representation of the solution in terms of a double integral as it shown by Begehr [1,2], some recursive relations in Fourier space, and Fast Fourier Transforms. The numerical evaluation of integrals at points on a polar coordinate grid by straightforward summation for the double integral would require floating point operation per point. Evaluation of such integrals has been optimized in this paper giving an asymptotic operation count of per point on the average. In actual implementation, the algorithm has even better computational complexity, approximately of the order of per point. The algorithm has the added advantage of working in place, meaning that no additional memory storage is required beyond that of the initial data. This paper is a result of application of many of the original ideas described in Daripa [3].

Algorithm for Fast Calculation of Hirzebruch-Jung Continued Fraction Expansions to Coding of Graph Manifolds

We present a new algorithm for the fast expansion of rational numbers into continued fractions. This algorithm permits to compute the complete set of integer Euler numbers of the sophisticate tree graph manifolds, which we used to simulate the coupling constant hierarchy for the universe with five fundamental interactions. Moreover, we can explicitly compute the integer Laplacian block matrix associated with any tree plumbing graph. This matrix coincides up to sign with the integer linking matrix (the main topological invariant) of the graph manifold corresponding to the plumbing graph. The need for a special algorithm appeared during computations of these topological invariants of complicated graph manifolds since there emerged a set of special rational numbers (fractions) with huge numerators and denominators;for these rational numbers, the ordinary methods of expansion in continued fraction became unusable.

Fast algorithm for simulation of normal and oblique penetration into limestone targets

A fast algorithm is proposed to predict penetration trajectory in simulation of normal and oblique penetration of a rigid steel projectile into a limestone target.The algorithm is designed based on the idea of isolation between the projectile and the target. Corresponding factors of influence are considered, including analytical load model,cratering effect, free surface effect, and separation-reattachment phenomenon. Besides, a method of cavity ring is used to study the process of cavity expansion. Further, description of the projectile's three-dimensional gesture is presented. As a result, the algorithm is coded for fast calculation, named PENE3D. A series of cases with selected normal and oblique penetrations are simulated by the algorithm. The predictions agree with the results of tests, showing that the proposed algorithm is fast and effective in simulation of the penetration process and prediction of the penetration trajectory.

Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness

A fast interactive segmentation algorithm of imagesequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from singleimage to imagesequences. Thus the segmentation of multiple objects from complex background and batch segmentation of imagesequences can be achieved. In addition, a postprocessing scheme is incorporated in this algorithm, which extracts smooth edge with onepixelwidth for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or imagesequences as well as manmade images quickly and reliably with only a little interaction.