MATLAB-application-projects

泽尼克多项式，像差 泽尼克多项式，像差泽尼克多项式，像差泽尼克多项式，像差(Zernike polynomials, Zernike polynomial aberration, aberration Zernike polynomials, Zernike polynomial aberration, aberration)

分析剖析器，深入的综述数据科学家和他们的工作是应用数据科学的方法到专业社区的结果。(Analyzing the Analyzers: An Introspective Survey of Data Scientists and their Work is the result of applying the methods of data science to our own professional community. )

matlab based object tracking

自己编的一个chase算法的小程序，只进行了一次迭代运算，关于多次迭代计算需进一步研究(developed an algorithm for small chase procedures, only a iteration, on the number of iterative calculations required further study)

人脸检测，使用的是matlab来做的，可以自由改动(facial detection)

实现二维的MUSIC算法，并精确计算出波达方向，并作出可视图形。(The two dimensional MUSIC algorithm, and calculate the direction of arrival, and make visual graphics)

这是一个潮流计算的程序。运用了牛顿—拉夫逊法。求出了各节点电压，功率分布。(This is a process flow calculation. The use of the Newton- Raphson method. Obtained each node voltage, power distribution.)

病态线性方程组的计算题，涉及Gauss消元法、雅可比迭代法、高斯-赛德尔迭代法、最速下降法和共轭梯度法。每一个方法，都编写一个m文件，封装成函数的形式。然后通过总的HilbLineEquSet.m文件来调用执行，画出误差曲线图，得到运行结果。总的Matlab程序流程，如下所示： 病态方程组的计算包括：HilbLineEquSet.m、gauss.m、jacobi.m、gauss_seidel.m、fastest_descend.m和conjugated_grad.m六个文件。 程序执行结果包括：求解结果、迭代次数、迭代误差数据、误差曲线图等。 (Morbid Linear Equations calculation problems involving Gauss elimination method, Jacobi' s iterative method, Gauss- Seidel iterative method, steepest descent method and conjugate gradient method. Each method, all the preparation of an m file, packaged in the form of a function. Then the total HilbLineEquSet.m file to invoke the implementation of draw error curve, to be running results. General Matlab program flow, as follows: the calculation of morbid equations include: HilbLineEquSet.m, gauss.m, jacobi.m, gauss_seidel.m, fastest_descend.m and conjugated_grad.m six documents. Procedures for implementation of the findings include: solving a result, the number of iterations, iterative error data, error curve and so on.)

说明：  马氏距离的仿射不变性删除误匹配特征点 对，据此可求取2幅源图像间的仿射变换参数(Mahalanobis distance of the affine invariant features remove the false matching points Yes, according to the source to obtain two parameter affine transformation between images)

Extended Kalman filter for trajectory prediction