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。

Fast algorithm for constructing neighbor-joining phylogenetic trees

To improve the performance of Saitou and Nei＇s algorithm （SN） and Studier and Keppler＇s improved algorithm （SK） for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computation, a fast algorithm is proposed. The proposed algorithm includes three techniques. First, a linear array A[N] is introduced to store the sum of every row of the distance matrix （the same as SK）, which can eliminate many repeated computations. Secondly, the value of A [i] is computed only once at the beginning of the algorithm, and is updated by three elements in the iteration. Thirdly, a very compact formula for the sum of all the branch lengths of operational taxonomic units （OTUs） i and j is designed, and the correctness of the formula is proved. The experimental results show that the proposed algorithm is from tens to hundreds times faster than SN and roughly two times faster than SK when N increases, constructing a tree with 2 000 OTUs in 3 min on a current desktop computer. To earn the time with the cost of the space and reduce the computations in the innermost loop are the basic solutions for algorithms with many loops.

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.

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.

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.

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

Although the genetic algorithm （GA） for structural optimization is very robust, it is very computationally intensive and hence slower than optimality criteria and mathematical programming methods. To speed up the design process, the authors present an adaptive reanalysis method for GA and its applications in the optimal design of trusses. This reanalysis technique is primarily derived from the Kirsch＇s combined approximations method. An iteration scheme is adopted to adaptively determine the number of basis vectors at every generation. In order to illustrate this method, three classical examples of optimal truss design are used to validate the proposed reanalysis-based design procedure. The presented numerical results demonstrate that the adaptive reanalysis technique affects very slightly the accuracy of the optimal solutions and does accelerate the design process, especially for large-scale structures.

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 finiteelement-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 finiteelement 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.

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 coded for fast calculation, named PENE3D. A presented. As a result, the algorithm is 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.

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.

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

A fast interactive segmentation algorithm of image-sequences 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 single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction.

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.

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.

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 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.

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.

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.

A fast algorithm for multivariate Hermite interpolation

Multivariate Hermite interpolation is widely applied in many fields, such as finite element construction, inverse engineering, CAD etc.. For arbitrarily given Hermite interpolation conditions, the typical method is to compute the vanishing ideal I （the set of polynomials satisfying all the homogeneous interpolation conditions are zero） and then use a complete residue system modulo I as the interpolation basis. Thus the interpolation problem can be converted into solving a linear equation system. A generic algorithm was presented in [18], which is a generalization of BM algorithm [22] and the complexity is O（τ^3） where r represents the number of the interpolation conditions. In this paper we derive a method to obtain the residue system directly from the relative position of the points and the corresponding derivative conditions （presented by lower sets） and then use fast GEPP to solve the linear system with O（（τ ＋ 3）τ^2） operations, where τ is the displacement-rank of the coefficient matrix. In the best case τ = 1 and in the worst case τ = [τ/n], where n is the number of variables.

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].