可以编译的有限元法求解偏微分源程序

说明：  数学建模最优路径问题及投资例题解答，通过matalb编程解决以上问题(Mathematical model interpolation algorithm, with the mathematical modeling, use of matble programming solve interpolation fitting mathematical modeling optimal path problem and investment examples solutions, through the matalb programming solve the above problem)

利用MP,OMP,COSAMP算法处理二维信号比较(comparative of compressive sensing using mp，omp，cosamp )

in this project data is hiding by LSB stegnography the shifting opertor is used to shift the data

matlab power flow toolbox with document

在双轮平衡车中进行极点配置的Matlab仿真的实验(Matlab simulation of pole placement in a two wheeled balancing vehicle)

说明：  传统MUSIC算法仿真，有很高的应用价值，也存在很多的误差，有待深入研究(Conventional MUSIC algorithm simulation, the application has a very high value, there are many errors to be in-depth study)

线性微分方程边值问题打靶算法Matlab程序，注意该算法只能完成二阶常微分方程双边值问题求解，至于其他形式的边值问题必须先转换到二阶形式(Linear Differential Equations with Boundary Value Shooting Algorithm Matlab program, note that the algorithm can only complete the second-order ordinary differential equation boundary value problem must first be converted to the second-order form of As for other forms of boundary value problems)

对SC-FDE采用不同UW（特殊字）情况下进行误码性能比较，UW类型分别为chu序列和Frank-Zadoff(For SC-FDE using different UW (special characters) for the case of error performance comparison, UW type sequences, respectively, and Frank-Zadoff chu)

这是Lam_Morley修正的弧长法matlab案例，有助于大家对弧长法的理解和学习(This is the Lam_Morley modified arc length method matlab case, help us to understand and Study on arc length method)

边缘预测提出了一种基于预测的、有一定自适应性的边缘检测方法。介绍了其原理和算法实现过程。通过计算两个相邻像素的灰度值的均值、均方差和梯度来预测下一个像素的灰度值,比较预测值和真实值来判断下一个像素是否是边界点。通过与现有同类算法的比较,证明了该算法的优越性(A predictive and adaptive edge detection method is proposed. The principle and implementation process of the algorithm are introduced. The gray value of the next pixel is predicted by calculating the mean, mean square deviation and gradient of the gray value of the two adjacent pixels. The prediction value and the real value are compared to determine whether the next pixel is a boundary point. The superiority of this algorithm is proved by comparing with the existing similar algorithms.)