PlateOfElasticStatic

说明：  用于在数值分析中，对于离散点进行拉格朗日差值拟合(Lagrangian difference fitting)

说明：  线性判别分析（LDA，全称Fisher Linear Discriminant Analysis）算法的C#实现源码，根据stprtool box for matlab中的LDA.m编写。用到MathNet库做相关的矩阵运算，使用zedgraph控制绘图。有简单的测试数据。( C# source code of linear discriminant analysis (LDA, full name of the Fisher Linear Discriminant Analysis) algorithm , according to LDA.m of stprtool box for matlab . Use MathNet library to do matrix operations,and use zedgraph control for drawing. Thers has a simple test data.)

利用SAR卫星在多个时刻的位置和速度信息，计算出任意象元成像时刻卫星的位置，拟合出SAR卫星的轨道模型。(Using SAR satellite in multiple time position and velocity information to calculate as the image element imaging time satellite position, fitting the SAR satellite orbital model.)

随机森林算法，适合初学者阅读，包括公式，资料，调试(Random forests algorithm, suitable for beginners to read, including formulas, data, commissioning)

Levenberg Marquardt算法的matlab代码,简洁无误,结构清晰,便于快速学习。( LevenbergMarquardt algorithm matlab code, simple and correct, clear structure, easy to learn quickly.)

汽车仿真模型，包含七自由度仿真模型、m文件和数学方程式(Car simulation model，Contains seven degrees of freedom simulation model m file and mathematical equations)

地球物理偏移相关程序包，能实现时间偏移、深度偏移、及逆时偏移等，编写语言：Matlab。(Geophysical migration coding package, time migration, depth migration, reverse time migration, the writing language: Matlab.)

说明：  用matlab实现的有限元工具箱，有平面空间梁单元，杆单元，实体单元等。(achieved using Matlab Toolbox FEM, graphic space beam elements, rod elements, entities modules.)

ABAQUS纤维增强复合材料损伤失效UMAT(ABAQUS UMAT subroutine for fiber-reinforced composite failure analysis)

为了提高三级倒立摆系统控制的响应速度和稳定性,在设计Mamdani 型模糊推理规则控制器控制倒立摆系统稳定的基础上, 设计了一种更有效率的基于Sugeno 型模糊推理规则的模糊神经网络控制器。该控制器使用BP 神经网络和最小二乘法的混 合算法进行参数训练,能够准确归纳输入输出量的模糊隶属度函数和模糊逻辑规则。通过与Mamdani 型控制器的仿真对比, 表明该Sugeno 型模糊神经网络控制器对三级倒立摆系统的控制具有良好的稳定性和快速性,以及较高的控制精度。(In order to improve the three-level control of inverted pendulum system response speed and stability, in the design of Mamdani-type fuzzy inference rules of the system controller to control the stability of inverted pendulum on the basis of a more efficient design based on Sugeno-type fuzzy inference rules of fuzzy neural network controller. The controller is the use of BP neural network and hybrid least squares training algorithm parameters can be accurately summed up the amount of input and output fuzzy membership function and fuzzy logic rules. Mamdani-type controller with a simulation comparison shows that the Sugeno-type fuzzy neural network controller for the three-tier control of inverted pendulum system with good stability and fast, as well as a higher control precision.)