Performance of the BEM solution in 3D acoustic wave scattering

A fixed cylindrical circular cavity and a cylindrical circular column of fluid of infinite length submerged in a homogeneous fluid medium, and subjected to a pressure point source, for which closed form solutions are known, are used to assess the performance of constant, linear and quadratic boundary elements in the analysis of acoustic scattering.This aim is accomplished by evaluating the error committed by the boundary element method (BEM) for a wide range of frequencies and wave numbers. First, the position of dominant BEM errors in the frequency versus spatial wave number domains are identified and related to the natural modes of vibration of the cylindrical circular inclusion. Then, the errors that occur by using constant, linear and quadratic elements are compared when the inclusion is modelled with the same number of nodes (i.e. maintaining computational cost). Finally, the importance of the position of the nodal points inside discontinuous boundary elements is analysed.     

Adaptive Recompression of -Matrices for BEM

The efficient treatment of dense matrices arising, e.g., from the finite element discretisation of integral operators requires special compression techniques. In this article, we use a hierarchical low-rank approximation, the so-called -matrix, that approximates the dense stiffness matrix in admissible blocks (corresponding to subdomains where the underlying kernel function is smooth) by low rank matrices. The low rank matrices are assembled by the ACA+ algorithm, an improved variant of the well-known ACA method. We present an algorithm that can determine a coarser block structure that minimises the storage requirements (enhanced compression) and speeds up the arithmetic (e.g., inversion) in the -matrix format. This coarse approximation is done adaptively and on-the-fly to a given accuracy such that the matrix is assembled with minimal storage requirements while keeping the desired approximation quality. The benefits of this new recompression technique are demonstrated by numerical examples.     

用无网格方法求解声波散射问题

在均匀介质中,对软表面障碍、时间调和声波散射问题归结为Helmholtz方程的Dirichlet外问题.应用无网格方法求解Helmholtz方程的Dirichlet外问题,并给出了一个数值例子,与Nystrom方法进行了对比,表明该方法是较精确的.     

Adaptive multilevel rough entropy evolutionary thresholding

In this study, comprehensive research into rough set entropy-based thresholding image segmentation techniques has been performed producing new and robust algorithmic schemes. Segmentation is the low-level image transformation routine that partitions an input image into distinct disjoint and homogenous regions using thresholding algorithms most often applied in practical situations, especially when there is pressing need for algorithm implementation simplicity, high segmentation quality, and robustness. Combining entropy-based thresholding with rough set results in the rough entropy thresholding algorithm.The authors propose a new algorithm based on granular multilevel rough entropy evolutionary thresholding that operates on a multilevel domain. The MRET algorithm performance has been compared to the iterative RET algorithm and standard k-means clustering methods on the basis of β-index as a representative validation measure. Performance in experimental assessment suggests that granular multilevel rough entropy threshold based segmentations - MRET - present high quality, comparable with and often better than k-means clustering based segmentations. In this context, the rough entropy evolutionary thresholding MRET algorithm is suitable for specific segmentation tasks, when seeking solutions that incorporate spatial data features with particular characteristics.     

Adaptive eigenspace for multi-parameter inverse scattering problems

A nonlinear optimization method is proposed for inverse scattering problems in the frequency domain, when the unknown medium is characterized by one or several spatially varying parameters. The time-harmonic inverse medium problem is formulated as a PDE-constrained optimization problem and solved by an inexact truncated Newton-type method combined with frequency stepping. Instead of a grid-based discrete representation, each parameter is projected to a separate finite-dimensional subspace, which is iteratively adapted during the optimization. Each subspace is spanned by the first few eigenfunctions of a linearized regularization penalty functional chosen a priori. The (small and slowly increasing) finite number of eigenfunctions effectively introduces regularization into the inversion and thus avoids the need for standard Tikhonov-type regularization. Numerical results illustrate the accuracy and efficiency of the resulting adaptive eigenspace regularization for single and multi-parameter problems, including the well-known Marmousi model from geosciences.     

Adaptive sparse grid multilevel methods for elliptic PDEs based on finite differences

We present a multilevel approach for the solution of partial differential equations. It is based on a multiscale basis which is constructed from a one-dimensional multiscale basis by the tensor product approach. Together with the use of hash tables as data structure, this allows in a simple way for adaptive refinement and is, due to the tensor product approach, well suited for higher dimensional problems. Also, the adaptive treatment of partial differential equations, the discretization (involving finite differences) and the solution (here by preconditioned BiCG) can be programmed easily. We describe the basic features of the method, discuss the discretization, the solution and the refinement procedures and report on the results of different numerical experiments.     

Analysis of a conjugated infinite element method for acoustic scattering

This work is devoted to a study of a conjugated infinite element method for Helmholtz problems in exterior domains. A formulation of this method with Lagrange multipliers defined on (semi-)infinite space is presented and analyzed in a domain decomposition context. The implementation aspects of this method in a parallel industrial acoustic software (SYSNOISE) are described in details. Numerical results show the computational efficiency of this method on acoustic scattering problems.     

水声传感器网络节点自适应加权定位算法

对水声传感器网络节点定位进行研究,针对水声传感器网络节点间测距精度不高的问题,提出一种水声传感器网络节点自适应加权定位算法。考虑到水声传感器网络节点间的测距误差随着节点间距离的增大而增大,算法改进了锚节点选择机制,并且对不同锚节点在定位测度中的权重进行加权,改进定位测度,提高了测距信息的利用效率。仿真实验表明该算法提高了节点定位精度。     

A GPGPU solution of the FMM near interactions for acoustic scattering problems

The Fast Multipole Method (FMM) is specially suitable for applications in which it is necessary to predict the acoustic scattering, e.g., aircraft noise control. This accelerated iterative method has two main parts, far interactions and near interactions. Near interactions are computationally intensive and they fit properly in the Single Instruction Multiple Threads paradigm. In this work, we present a heterogeneous parallel solution in which the near interactions are computed using Graphical Processing Units (GPUs). The performance of the proposed solution is proved using a workstation with one NVIDIA GTX480 GPU and a cluster that consists of 32 nodes HP BL465c with an Infiniband network.     

压缩感知下的自适应声源定位估计

声源定位是一个应用非常广泛的研究课题。针对阵列定位精度不高的问题,提出一种基于压缩感知的声源定位算法。通过构建冗余字典,该算法将网络中的多个未知源节点的位置作为一个系数向量,然后采用稀疏贝叶斯学习算法估计声源位置。为了增快算法的运行速度,提出一种有效的多分辨率字典构建方法,并迭代地减小定位空间,提高定位精度。实验结果显示,基于压缩感知的声源定位算法可以改善多源节点的定位能力,且有效地减少所需的传感器节点。此外,与基于子空间的算法比较显示,该算法的性能更优越。     

Imaging of layered media in inverse scattering problems for an acoustic wave equation

Two-dimensional (2D) inverse scattering problems for the acoustic wave equation consisting of obtaining the density and acoustic impedance of the medium are considered. A necessary and sufficient condition for the unique solvability of these problems in the form of the law of energy conservation has been established. It is proved that this condition is that for each pulse oscillation source located on the boundary of a half-plane, the energy flow of the scattered waves is less than the energy flux of waves propagating from the boundary of this half-plane. This shows that for inverse dynamic scattering problems in acoustics and geophysics when the law of energy conservation holds it is possible to determine the elastic density parameters of the medium. The obtained results significantly increase the class of mathematical models currently used in solving multidimensional inverse scattering problems. Some specific aspects of interpreting inverse problems solutions are considered.     

Adaptive detection of spatial point event outliers using multilevel constrained Delaunay triangulation

Spatial outlier detection is a research hot spot in the field of spatial data mining. Because of the lack of specific research on spatial point events, this study presents an adaptive approach for spatial point events outlier detection (SPEOD) using multilevel constrained Delaunay triangulation. First, the spatial proximity relationships between spatial point events are roughly captured by Delaunay triangulation. Then, three-level constraints are described and used to refine spatial proximity relationships with the consideration of statistical characteristics. Finally, those spatial point events connected by remaining edges are gathered to form a series of subgraphs. Those subgraphs containing very few point events are regarded as spatial outliers. Experiments on both synthetic and real-world spatial data sets are used to show that the proposed SPEOD algorithm can detect various types of spatial point event outliers with high efficiency. Moreover, there is no need to input any parameter in SPEOD.     

基于水声信道状态的自适应差错控制

水声信道具有时变、环境噪声高、传播时延大、信道带宽窄等特点,以致水声通信的可靠性不高(接收数据发生错误)。目前的解决办法主要有自动请求重传和前向纠错,但是这两种方式均不能在所有信道状态下保持较高的接收吞吐量。提出了一种自适应差错控择方法,其中包括一种利用信道误码率计算吞吐量的方法,并且采用自适应线性预测方法预测信道误码率,根据信道误码率选择合适的差错控制方式。仿真结果表明,采用该选择方法能够在所有的信道状态下保持较高的接收端吞吐量,提高水声通信的性能。     

Hierarchical LU Decomposition-based Preconditioners for BEM

The adaptive cross approximation method can be used to efficiently approximate stiffness matrices arising from boundary element applications by hierarchical matrices. In this article an approximative LU decomposition in the same format is presented which can be used for preconditioning the resulting coefficient matrices efficiently. If the LU decomposition is computed with high precision, it may even be used as a direct yet efficient solver.     

Efficient iterative algorithms for the stochastic finite element method with application to acoustic scattering

In this study, we describe the algebraic computations required to implement the stochastic finite element method for solving problems in which uncertainty is restricted to right-hand side data coming from forcing functions or boundary conditions. We show that the solution can be represented in a compact outer product form which leads to efficiencies in both work and storage, and we demonstrate that block iterative methods for algebraic systems with multiple right-hand sides can be used to advantage to compute this solution. We also show how to generate a variety of statistical quantities from the computed solution. Finally, we examine the behavior of these statistical quantities in one setting derived from a model of acoustic scattering.     

基于无线传感器网络的自适应声源定位算法

基于声源能量的无线传感器网络（ WSNs）最大似然定位算法抗噪声干扰能力强,定位精度高,同时适用于多个目标定位,但是计算量大,不适用于实时定位。针对现有算法的缺点,提出了一种基于自适应迭代的最大似然定位算法。该算法将代价函数作为目标函数,在给定的梯度误差范围内自适应地搜索目标位置。为了提高算法的收敛速度和定位精度,提出了基于Sigmoid函数的变步长的搜索算法。仿真实验结果表明：与最大似然定位算法相比,自适应迭代算法运算量小,定位精度高,能满足对目标定位精度和速度要求较高的场合,具有一定的实际应用意义。     

保形（Conformal）结构互连电容的BEM模拟

介绍了一种基于扫描线的复杂保形介质结构快速生成算法,该算法应用多边形的扩展运算和集合运算形成保形介质,同时处理保形介质听 凹槽,并已实现了边界元素法三维互连寄生电容提取软件B3D中,数值结果表明,该算法可靠,并有很高效率。     

Leader-follower strategies for multilevel systems

Sequential strategies for dynamic systems with multiple decision makers and multiple performance indices are surveyed and reviewed. These strategies are generalizations of Stackelberg or leader-follower strategies for two-person games. The review includes structures with one coordinator and several second-level decision makers, and linear hierarchical structures with only one decision maker at each level Several information structures are considered.     

自适应视听信息融合用于抗噪语音识别

为了提高噪音环境中语音识别的准确性和鲁棒性,提出了基于自适应视听信息融合的抗噪语音识别方法,视听信息在识别过程中具有变化的权重,动态的自适应于环境输入的信噪比．根据信噪比和反馈的识别性能,通过学习自动机计算视觉信息的最优权重;根据视听信息的特征向量,利用隐马尔科夫模型进行视听信息的模式匹配,并根据最优权重组合视觉和声音隐马尔科夫模型的决策,获得最终的识别结果．实验结果表明,在各种噪音水平下,自适应权重比不变权重的视听信息融合的语音识别性能更优．