matlabOfficialStudyManual

说明：  图像读取子程序 图像保存子程序 频域增强子程序(Save the image to read the image subroutine subroutine subroutine enhanced frequency domain)

解微分方程（组）的定步长四阶龙格库塔法算法源代码(Solution of differential equations (Group) of fixed step size fourth-order Runge-Kutta method algorithm source code)

programation matlab de tp de traitement

关于迭代学习算法，分析了收敛速度,开闭环二阶迭代学习控制算法(The Analysis of Convergence Speed for an Openand Closed Loop Second Order Iterative Learning Control Algorithm)

说明：  我的matlab实验 MATLAB运算基础 选择结构程序设计 循环结构程序设计 函数文件 高层绘图操作 数据处理与多项式计算 数值微积分与方程数值求解 符号计算基础与符号微积分(My matlab choice experiment based on the structure MATLAB programming operations structured programming cycle function file data processing and high-level drawing operations polynomial equation calculated with numerical integration and numerical solution based on symbolic computation and symbol calculus)

Implementation of brute force algorithm of pattern recognition.

Expectation maximisation with principal component analysis

The alogrithm employed in this toolbox for determining Lyapunov exponents is according to the algorithms proposed in [1] A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano "Determining Lyapunov Exponents from a Time Series," Physica D, Vol. 16, pp. 285-317, 1985. [2] J. P. Eckmann and D. Ruelle, "Ergodic Theory of Chaos and Strange Attractors," Rev. Mod. Phys., Vol. 57, pp. 617-656, 1 The algorithm given in [1] is used for first-order systems while the QR-based algorithm proposed in [2] is applied for higher order systems. by Steve W. K. SIU, July 5, 1998. (The alogrithm employed in this toolbox for determining Lyapunov exponents is according to the algorithms proposed in [1] A. Wolf, J. B. Swift, H. L. Swinney, and J. A. Vastano, "Determining Lyapunov Exponents from a Time Series," Physica D, Vol. 16, pp. 285-317, 1985. [2] J. P. Eckmann and D. Ruelle, "Ergodic Theory of Chaos and Strange Attractors," Rev. Mod. Phys., Vol. 57, pp. 617-656, 1985. The algorithm given in [1] is used for first-order systems while the QR-based algorithm proposed in [2] is applied for higher order systems. by Steve W. K. SIU, July 5, 1998. )

说明：  卡尔曼滤波的一个典型实例是从一组有限的，对物体位置的，包含噪声的观察序列预测出物体的坐标位置及速度. 在很多工程应用(雷达, 计算机视觉)中都可以找到它的身影. 同时，卡尔曼滤波也是控制理论以及控制系统工程中的一个重要话题. 　　比如,在雷达中,人们感兴趣的是跟踪目标,但目标的位置,速度,加速度的测量值往往在任何时候都有噪声.卡尔曼滤波利用目标的动态信息,设法去掉噪声的影响,得到一个关于目标位置的好的估计。这个估计可以是对当前目标位置的估计(滤波),也可以是对于将来位置的估计(预测)，也可以是对过去位置的估计(插值或平滑). (kalman filter in matlab)

实现数字水印提取 变换 分数级数变换压缩(watermark)