vuel_springs_3d_jumpDofs

ABAQUS 显式计算时 用户自定义子材料程序 VUMAT源代码，(User defined subrutine of ABAQUS explicit analysis)

The following is an example of how Microsoft Solver Foundation can be used to solve a constraint satisfaction problem (CSP) like generating a typical Sudoku problem. Sudoku http://www.codeproject.com/Articles/419389/Sudoku-using-Microsoft-solver-foundation In this article I do not attempt to explain everything there is to know about constraint satisfaction problems, but I will go over the concepts in the hope that even if you have never heard of CSP you will still get the idea.

说明：  基尔霍夫近似方法，计算目标的双站散射系数。参考乌拉比的微波遥感。(Kirchhoff s approximation method to calculate the bistatic scattering coefficient of the target. Refer to the Orabi microwave remote sensing.)

说明：  弹性波中瑞雷波的正演计算。求解多层瑞雷波频散曲线。计算速度快。（专业小软件）(elastic wave Rayleigh wave to the calculation. Solving multi-storey Rayleigh wave dispersion curves. Calculation speed. (Professional small software))

说明：  上数据挖掘课的课件，是EM算法的，其中还包括最大似然值，最大似然估计，以及cluster(data mining,EM Algorithm ,Likelihood, Mixture Models and Clustering )

这是几篇关于粒计算在故障诊断中的应用，对学习粒计算的应用很有帮助。(This is a few on Granular Computing in Fault Diagnosis of learning the application of granular computing helpful.)

使用龙格-库塔间断Galerkin方法（RKDG）求解无粘流动Euler方程的程序，适用于计算流体力学RKDG方法的学习和研究。(Using the discontinuous Galerkin method (DG) for solving inviscid flow Euler equations procedures applicable to DG methods of study and research.)

国外最近的一篇变步长nlms仿真，该文件有文中的几种仿真(Recent foreign nlms a variable step simulation, there is the text of the document of several simulation)

本书介绍了XFEm在结构件的断裂分析中的应用(this book introduces the application of XFEM in the field of fracture analysis)

针对多径效应的影响，提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号，采用单样本数信号矢量构造了一个前后向矩阵束，并利用两个酉矩阵对该矩阵束进行降维处理，最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵，可在低 信噪比和单样本数情况下，有效地克服多径效应，实现同时多目标低仰角估计，相比最大似然算法，避免了谱峰搜索，计算量小。仿真结果验证了该算法的有效性。(To overcome the multipath effect, a fast algorithm for low elevation estimation for MIMO radar via matrix pencil is proposed. The signals both in transmit multipath and receive multipath are considered. Firstly, a forward-backward matrix pencil is formed based on the single-sampled vector. Secondly, the reduced-dimensional processing is applied to the matrix pencil via two unitary matrices. Finally, the generalized eigen-decomposition is employed to estimate the low elevation in multipath environments directly. Without the covariance matrix estimation, the proposed method can overcome multipath effect effectively in case of low SNR and estimate multi-target simultaneously. Compared with Maximum Likelihood (ML) method, it avoids spectrum peak searching and reduces the computational burden. Numerical results verify the effectiveness of this method)