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 Fast Algorithm for Phase Grating Preparation by Real Space Method

Based on a definitely integral formula, an expression of calculating atomic potential distribution function U(r) in a unit cell is derived as follows: Making use of this expression to calculate the phase grating in high resolution image simulation can greatly reduce.the calculating time. In this paper, the derivation of the expression is introduced, and then the computer routine is explained in details. Finally the potential projection map of Mg44Rh7 along [001] direction is shown as an illustration. All operations are carried out in real space, so we call the calculation method as the real space 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 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 for Matching Remote Scene Images

An iterative algorithm to calculate mutual correlation using hierarchical key points and the search space mark principle is proposed. An effective algorithm is designed to improve the matching speed. By hi-erarchical key point algorithm and mutual correlation coefficients of the matching images, the important points can be iteratively calculated in the images hierarchically, and the correlation coefficient can be ob-tained with satisfactory precision. Massive spots in the parameter space which are impossible to match can be removed by the search space mark principle. Two approximate continuities in the correlation image matching process, the image gray level distribution continuity and the correlation coefficient value in the parameter space continuity, are considered in the method. The experiments show that the new algorithm can greatly enhance matching speed and achieve accurate matching results.

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 Improving the Visual Distance in Fog

Images captured outdoor usually degenerate because of the bad weather conditions,among which fog,one of the widespread phenomena,affects the video quality greatly.The physical features of fog make the video blurred and the visible distance shortened,seriously impairing the reliability of the video system.In order to satisfy the requirement of image processing in real-time,the normal distribution curve fitting technology is used to fit the histogram of the sky part and the region growing method is used to segment the region of sky.As for the non-sky part,a method of self-adaptive interpolation to equalize the histogram is adopted to enhance the contrast of the images.Experiment results show that the method works well and will not cause block effect.

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].

Fast Algorithm for DOA Estimation with Partial Covariance Matrix and without Eigendecomposition

A fast algorithm for DOA estimation without eigendecomposition is proposed. Unlike the available propagation method (PM), the proposed method need only use partial cross-correlation of array output data, and hence the computational complexity is further reduced. Moreover, the proposed method is suitable for the case of spatially nonuniform colored noise. Simulation results show the performance of the proposed method is comparable to those of the existing PM method and the standard MUSIC method.

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。

A Fast Algorithm for Solving CNOP and Associated Target Observation Tests

Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studying predictability and sensitivity among other issues in nonlinear systems. This is because the CNOP is able to represent, while the LSV is unable to deal with, the fastest developing perturbation in a nonlinear system. The wide application of this new method, however, has been limited due to its large computational cost related to the use of an adjoint technique. In order to greatly reduce the computational cost, we hereby propose a fast algorithm for solving the CNOP based on the empirical orthogonal function （EOF）. The algorithm is tested in target observation experiments of Typhoon Matsa using the Global/Regional Assimilation and PrEdiction System （GRAPES）, an operational regional forecast model of China. The effectivity and feasibility of the algorithm to determine the sensitivity （target） area is evaluated through two observing system simulation experiments （OSSEs）. The results, as expected, show that the energy of the CNOP solved by the new algorithm develops quickly and nonlinearly. The sensitivity area is effectively identified with the CNOP from the new algorithm, using 24 h as the prediction time window. The 24-h accumulated rainfall prediction errors （ARPEs） in the verification region are reduced significantly compared with the ＂true state,＂ when the initial conditions （ICs） in the sensitivity area are replaced with the ＂observations.＂ The decrease of the ARPEs can be achieved for even longer prediction times （e.g., 72 h）. Further analyses reveal that the decrease of the 24-h ARPEs in the verification region is attributable to improved simulations of the typhoon＇s initial warm-core, upper level relative vorticity, water vapor conditions, etc., as a result of the updated ICs in the sensitivity area.

A fast algorithm for determining the linear complexity of a binary sequence with period 2~np^m

An efficient algorithm for determining the linear complexity and the minimal polynomial of a binary sequence with period 2npm is proposed and proved, where 2 is a primitive root modulo p2. The new algorithm generalizes the algorithm for computing the linear complexity of a binary sequence with period 2' and the algorithm for computing the linear complexity of a binary sequence with period pn, where 2 is a primitive root modulo p2.

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.

Fast algorithm for viscous Cahn-Hilliard equation

The main purpose of this paper is to solve the viscous Cahn-Hilliard equation via a fast algorithm based on the two time-mesh(TT-M)finite element(FE)method to ease the problem caused by strong nonlinearities.The TT-M FE algorithm includes the following main computing steps.First,a nonlinear FE method is applied on a coarse time-meshτ_(c).Here,the FE method is used for spatial discretization and the implicit second-orderθscheme(containing both implicit Crank-Nicolson and second-order backward difference)is used for temporal discretization.Second,based on the chosen initial iterative value,a linearized FE system on time fine mesh is solved,where some useful coarse numerical solutions are found by Lagrange’s interpolation formula.The analysis for both stability and a priori error estimates is made in detail.Numerical examples are given to demonstrate the validity of the proposed algorithm.Our algorithm is compared with the traditional Galerkin FE method and it is evident that our fast algorithm can save computational time.

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.

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.

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.