Multiple sparse priors technique with optimized patches for brain source localization

Localizing brain neural activity using electroencephalography (EEG) neuroimaging technique is getting increasing response from neuroscience researchers and medical community. It is due to the fact that brain source localization has a variety of applications for diagnoses of various brain disorders. This problem is ill-posed in nature because an infinite number of source configurations can produce the same potential at the head surface. Recently, a new technique that is based on Bayesian framework, called the multiple sparse priors (MSP), was proposed as a solution to this problem. The MSP develops the solution for source localization using the current densities associated with dipoles in terms of prior source covariance matrix and sensor covariance matrix, respectively. Then, it uses the maximization of the cost function of the free energy under the assumption of a fixed number of hyperparameters or patches in order to obtain the elements of prior source covariance matrix. This research work aims to further enhance the maximization process of MSP with regard to the free energy by considering a variable number of patches. This will lead to a better estimation of brain sources in terms of localization errors. The performance of the modified MSP with a variable number of patches is compared with the original MSP using simulated and real-time EEG data. The results show a significant improvement in terms of localization errors.     

EEG source localization using a sparsity prior based on Brodmann areas

Localizing the sources of electrical activity in the brain from electroencephalographic (EEG) data is an important tool for noninvasive study of brain dynamics. Generally, the source localization process involves a high‐dimensional inverse problem that has an infinite number of solutions and thus requires additional constraints to be considered to have a unique solution. In this article, we propose a novel method for EEG source localization. The proposed method is based on dividing the cerebral cortex of the brain into a finite number of “functional zones” which correspond to unitary functional areas in the brain. To specify the sparsity profile of human brain activity more concisely, the proposed approach considers grouping of the electrical current dipoles inside each of the functional zones. In this article, we investigate the use of Brodmann's areas as the functional zones while sparse Bayesian learning is used to perform sparse approximation. Numerical experiments are conducted on a realistic head model obtained from segmentation of MRI images of the head and includes four major compartments namely scalp, skull, cerebrospinal fluid (CSF), and brain with relative conductivity values. Three different electrode setups are tested in the numerical experiments. The results demonstrate that the proposed approach is quite promising in solving the EEG source localization problem. In a noiseless environment with 71 electrodes, the proposed method was found to accurately locate up to 6 simultaneously active sources with accuracy >70%.     

Interest points localization for brain image using landmark‐annotated atlas

The localization of clinically important points in brain images is crucial for many neurological studies. Conventional manual landmark annotation requires expertise and is often time‐consuming. In this work, we propose an automatic approach for interest point localization in brain image using landmark‐annotated atlas (LAA). The landmark detection procedure is formulated as a problem of finding corresponding points of the atlas. The LAA is constructed from a set of brain images with clinically relevant landmarks annotated. It provides not only the spatial information of the interest points of the brain but also the optimal features for landmark detection through a learning process. Evaluation was performed on 3D magnetic resonance (MR) data using cross‐validation. Obtained results demonstrate that the proposed method achieves the accuracy of ～ 2 mm, which outperforms the traditional methods such as block matching technique and direct image registration. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 145–152, 2012     

基于改进FISTA的高分辨率声源定位方法

为提高快速迭代收缩阈值算法(Fast Iterative Shrinkage-Thresholding Algorithm, FISTA)在反卷积波束形成中的空间分辨率以及计算速度,采用基于快速傅里叶变换的声学模型,引入过松弛方法和“贪婪”重启策略,提出两种改进的快速迭代收缩阈值算法,即基于快速傅里叶变换的过松弛单调快速迭代收缩阈值算法(Over-relaxed MonotoneFast Iterative Shrinkage-Thresholding Algorithm based on Fast Fourier Transform, FFT-OMFISTA)和基于快速傅里叶变换的“贪婪”快速迭代收缩阈值算法("Greedy" Fast Iterative Shrinkage-Thresholding Algorithm based on Fast FourierTransform, FFT-GFISTA),并应用于反卷积波束形成的求解过程中。设计了单声源和双声源的仿真与实验,验证了所提算法的有效性与优越性。结果表明,两种所提算法都具有良好的性能,都能在声源定位中实现更高的空间分辨率以及更快的计算速度。     

加权稀疏信号重构的近场源定位方法

针对近场源定位问题,提出了一种使用加权L1范数优化进行稀疏信号重构的近场源定位方法。该定位方法分步完成目标的方位和距离估计。为了避免二维优化问题出现,首先利用均匀线阵的对称特性,通过菲涅尔近似,将二维参数估计的近场定位问题转换为类远场阵列的一维参数估计问题,接着将该一维参数估计问题转换为稀疏信号重构问题,通过类MUSIC权向量的构造,使用加权L1范数优化方法重构稀疏空间谱得到目标波达方向;在得到信号波达方向之后,再利用稀疏信号重构的思想求解信号源到阵列的距离。最后,通过数字仿真验证了算法在估计精度和分辨率等方面的优良性能。     

Acoustic emission source localization technique based on least squares support vector machine by using FBG sensors

An intelligent acoustic emission (AE) source localization technique by using fiber Bragg grating (FBG) sensors was investigated. Four FBGs sensing network was established for detecting the AE signal. And power intensity demodulation method was initialized employing narrow-band tunable laser. The intelligent AE source localization method was proposed based on wavelet transform, cross-correlation analysis, and least squares support vector machines (LS-SVM). LS-SVM modal’s input is signal time difference and output is AE source position. The location experiments were carried out on a 500 mm × 500 mm × 2 mm aluminum alloy plate. The results showed that the AE source position abscissa and ordinate localization errors are all less than 10 mm. The maximum and average localization errors are 8.65 and 6.78 mm, respectively. The research results provided a novel method for AE source localization by using FBG sensors.     

Chan算法在海上声源定位测量中的应用

针对到达时间差（Time Difference of Arrival,TDOA）体制下海上声源定位测量问题,研究了Chan算法在定位测量中的应用。建立了基于TDOA体制的海上声源被动定位模型,推导了Chan算法求解TDOA定位方程的步骤,采用了蒙特卡洛数值方法对Chan算法与初始值选择真值的泰勒（Taylor）级数展开法在不同阵元数条件下的定位精度进行了比较,得出了Chan算法在海上声源定位测量中应用条件及基阵布设原则。仿真结果表明,在一定条件下,Chan算法可应用于海上声源定位测量且定位精度较高,研究结果可为海上声源测量系统定位算法设计及基站布设提供参考依据。     

A class of variational strain‐localization finite elements

We present a class of finite elements for capturing sub‐grid localization processes such as shear bands and void sheets. The elements take the form of a double surface and deform in accordance with an arbitrary constitutive law. In particular they allow for the development of displacement and velocity jumps across volume element boundaries. The thickness of the localized zone is set by an additional field variable which is determined variationally. The localization elements are inserted, and become active, only when localized deformations become energetically favourable. The implementation presented in this work is three‐dimensional and allows for finite deformations. The versatility and predictive ability of the method are demonstrated through a simple shear test and the simulation of the dynamic impact of a pre‐notched C300 steel sample by a steel projectile. Copyright © 2004 John Wiley & Sons, Ltd.     

基于声压幅度比的多声源分离定位决策研究

利用声压幅度比模型,提出了一种基于声压幅度比的多声源分离定位方法,该方法利用盲信号分离算法实现混合声源信号的分离,根据谱估计的相似度确定接收信号中各声源的分配情况,结合幅度差异因子获得传感器的声源信号分布,再通过单声源的声压幅度比模型确定声源位置,实现多声源定位。由于盲信号分离算法比较成熟,且实际中的声源信号大多为非高斯,因而满足盲信号分离条件。该方法具有实用强、应用性广等特点,对其它分离、定位问题也有借鉴作用。     

Robust brain MRI denoising and segmentation using enhanced non‐local means algorithm

Image denoising is an integral component of many practical medical systems. Non‐local means (NLM) is an effective method for image denoising which exploits the inherent structural redundancy present in images. Improved adaptive non‐local means (IANLM) is an improved variant of classical NLM based on a robust threshold criterion. In this paper, we have proposed an enhanced non‐local means (ENLM) algorithm, for application to brain MRI, by introducing several extensions to the IANLM algorithm. First, a Rician bias correction method is applied for adapting the IANLM algorithm to Rician noise in MR images. Second, a selective median filtering procedure based on fuzzy c‐means algorithm is proposed as a postprocessing step, in order to further improve the quality of IANLM‐filtered image. Third, different parameters of the proposed ENLM algorithm are optimized for application to brain MR images. Different variants of the proposed algorithm have been presented in order to investigate the influence of the proposed modifications. The proposed variants have been validated on both T1‐weighted (T1‐w) and T2‐weighted (T2‐w) simulated and real brain MRI. Compared with other denoising methods, superior quantitative and qualitative denoising results have been obtained for the proposed algorithm. Additionally, the proposed algorithm has been applied to T2‐weighted brain MRI with multiple sclerosis lesion to show its superior capability of preserving pathologically significant information. Finally, impact of the proposed algorithm has been tested on segmentation of brain MRI. Quantitative and qualitative segmentation results verify that the proposed algorithm based segmentation is better compared with segmentation produced by other contemporary techniques.     

基于麦克风阵列的三维声源定位算法及其实现

从系统的角度对真实声场环境下基于到达时间差的的声源定位算法进行了研究,提出了一种改进的互功率谱相位（CSP）时延估计算法,在此基础上,提出了一种用于定位估计的基于球形差值（SI）的随机梯度下降（LMS）算法。为了验证算法的有效性,实际构建了三维空间中的点声源定位系统。实验结果表明所提出的算法具有较高的定位精度。     

基于鸡群算法的近场声源三维定位MUSIC算法

针对三维多重信号分类（Multiple Signal Classification，MUSIC）算法估计声源位置时计算速度慢，计算量大等缺点，提出了一种基于鸡群优化（Chicken Swarm Optimization，CSO）算法的近场声源三维定位算法。首先建立近场声源信号接收的数学模型，并选取三维MUSIC算法中的空间谱函数为文章算法中的适应度函数。通过不断迭代和局部搜索，以适应度值为指标对鸡群个体进行排序，最终得到最优鸡群个体的位置，即近场待测声源的坐标。仿真和实验结果表明：文中算法具有定位精度高、计算效率高、实时性好等优点，文中算法的平均用时仿真时为三维MUSIC算法平均用时的1.9%，实验时为三维MUSIC算法用时的3.2%。     

Numerical analysis of localization using a viscoplastic regularization: influence of stochastic material defects

The finite element reliability method is applied to evaluate the effects of stochastic imperfections on the localization behaviour of elasto‐viscoplastic softening solids. Material properties as the Young's modulus, the softening modulus and the initial yield stress are considered to be random fields. Failure criteria are defined for the peak load and the dissipated energy. Likely configurations of imperfections which lead to failure are obtained and the nature and relative importance of the corresponding localization patterns are analyzed. Copyright © 1999 John Wiley & Sons, Ltd.     

Analysis of photonic crystals using the hybrid finite‐element/finite‐difference time domain technique based on the discontinuous Galerkin method

Two‐dimensional photonic crystal structures are analyzed by a recently developed hybrid technique combining the finite‐element time‐domain (FETD) method and the finite‐difference time‐domain (FDTD) method. This hybrid FETD/FDTD method uses the discontinuous Galerkin method as framework for domain decomposition. To the best of our knowledge, this is the first hybrid FETD/FDTD method that allows non‐conformal meshes between different FETD and FDTD subdomains. It is also highly parallelizable. These properties are very suitable for the computation of periodic structures with curved surfaces. Numerical examples for the computation of the scattering parameters of two‐dimensional photonic bandgap structures are presented as applications of the hybrid FETD/FDTD method. Numerical results demonstrate the efficiency and accuracy of the proposed hybrid method. Copyright © 2012 John Wiley & Sons, Ltd.     

衍射现象对活塞式声源超声场分布的影响

超声波由于其良好的指向性,可被广泛应用于海洋探测与开发、无损检测与评估、医学诊断等应用领域。基于KZK方程,利用频域有限差分方法对衍射现象进行分析,计算了活塞式声源的基波和高次谐波声场,发现高次谐波和基波具有类似的声场分布特性,并且谐波阶次越高,径向扩散越少,声场特性越好。研究获得了超声波在空气中传播的声场特性,分析了基波及各次谐波的指向性优劣以及传播范围的大小。在研究的过程中,利用MATLAB等数学工具,对研究结果进行了数值计算和模拟。以上结果为研究超声波的声场特性提供了一定的参考,对研究超声波声场的指向性有着实际性的意义。     

Three‐dimensional grayscale‐free topology optimization using a level‐set based r‐refinement method

In this paper, we propose a three‐dimensional (3D) grayscale‐free topology optimization method using a conforming mesh to the structural boundary, which is represented by the level‐set method. The conforming mesh is generated in an r‐refinement manner; that is, it is generated by moving the nodes of the Eulerian mesh that maintains the level‐set function. Although the r‐refinement approach for the conforming mesh generation has many benefits from an implementation aspect, it has been considered as a difficult task to stably generate 3D conforming meshes in the r‐refinement manner. To resolve this task, we propose a new level‐set based r‐refinement method. Its main novelty is a procedure for minimizing the number of the collapsed elements whose nodes are moved to the structural boundary in the conforming mesh; in addition, we propose a new procedure for improving the quality of the conforming mesh, which is inspired by Laplacian smoothing. Because of these novelties, the proposed r‐refinement method can generate 3D conforming meshes at a satisfactory level, and 3D grayscale‐free topology optimization is realized. The usefulness of the proposed 3D grayscale‐free topology optimization method is confirmed through several numerical examples. Copyright © 2017 John Wiley & Sons, Ltd.     

A structural optimization method based on the level set method using a new geometry‐based re‐initialization scheme

Structural optimization methods based on the level set method are a new type of structural optimization method where the outlines of target structures can be implicitly represented using the level set function, and updated by solving the so‐called Hamilton–Jacobi equation based on a Eulerian coordinate system. These new methods can allow topological alterations, such as the number of holes, during the optimization process whereas the boundaries of the target structure are clearly defined. However, the re‐initialization scheme used when updating the level set function is a critical problem when seeking to obtain appropriately updated outlines of target structures. In this paper, we propose a new structural optimization method based on the level set method using a new geometry‐based re‐initialization scheme where both the numerical analysis used when solving the equilibrium equations and the updating process of the level set function are performed using the Finite Element Method. The stiffness maximization, eigenfrequency maximization, and eigenfrequency matching problems are considered as optimization problems. Several design examples are presented to confirm the usefulness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

Gradient‐enhanced damage modelling of high‐cycle fatigue

Continuum damage mechanics can be used to model the initiation and growth of fatigue cracks. However, finite element analyses using standard fatigue damage formulations exhibit an extreme sensitivity to the spatial discretisation of the problem. The mesh sensitivity is caused by the fact that the underlying continuum model predicts instantaneous, perfectly brittle crack growth as soon as a crack has been initiated. The growth of damage localizes in a vanishing volume during this instantaneous growth. This localization is not so much due to loss of ellipticity of the problem, but is caused by the fact that the damage rate is singular at the crack tip. The damage rate singularity can be removed by the introduction of higher‐order deformation gradients in the constitutive modelling. As a result, crack growth at a finite rate and with a positive amount of energy dissipation is predicted. Finite element analyses converge to this solution and are thus no longer pathologically dependent on the spatial discretization. Copyright © 2000 John Wiley & Sons, Ltd.     

A geometrical‐based contact algorithm using a barrier method

Most methods employed in the numerical solution of contact problems in finite element simulations rely on equality‐based optimization methods. Typically, a gap function which is non‐differentiable at the point of contact is used in these kind of approaches. The gap function can be seen as the Macaulay bracket of some distance function, where the latter is differentiable at the point of contact. In this article, we propose to use the distance function directly instead of using the gap function. This will give rise to a formulation involving inequality constraints. This approach eliminates the artificially introduced non‐differentiability. To this end we propose a barrier algorithm as the method of choice to solve the problem. The method originates in optimization literature, where convergence proofs for the method are available. Copyright © 2001 John Wiley & Sons, Ltd.     

Equivalent localization element for crack band approach to mesh‐sensitivity in microplane model

The paper presents in detail a novel method for finite element analysis of materials undergoing strain‐softening damage based on the crack band concept. The method allows applying complex material models, such as the microplane model for concrete or rock, in finite element calculations with variable finite element sizes not smaller than the localized crack band width (corresponding to the material characteristic length). The method uses special localization elements in which a zone of characteristic size, undergoing strain softening, is coupled with layers (called ‘springs’) which undergo elastic unloading and are normal to the principal stress directions. Because of the coupling of strain‐softening zone with elastic layers, the computations of the microplane model need to be iterated in each finite element in each load step, which increases the computer time. Insensitivity of the proposed method to mesh size is demonstrated by numerical examples. Simulation of various experimental results is shown to give good agreement. Copyright © 2004 John Wiley & Sons, Ltd.