TF-analysis

本代码是是基于离散余弦变化的数字水印算法，通过Matlab来实现。对学习水印有很大的帮助！(DCT)

最优化中非线性规划中改进的单纯形算法matlab实现，可修改参数(nonlinear optimization program to improve the simplex algorithm Matlab, which could be revised parameters)

基于LFSR和混沌理论的伪随机序列生成方法 (Pseudo-random sequences generating method based on LFSR and chaos theory)

十字路口车流通量及车身颜色的统计通过MATLAB创建系统对象，用于读入待处理视频，用于色彩空间转换、检测出包含汽车运动的图像块、用高斯混合模型检测背景、对检测出的运动车辆进行框画、标注检测到车辆的个数用于显示结果。颜色提取算法采用 RGB 颜色模型，利用MATLAB进行仿真(Crossing the circulation of the car and body color statistics by MATLAB to create object system, used to read the video to be processed and used for color space conversion, detect image blocks comprising the sports car, with Gaussian mixture model background detection to detect the moving vehicle frame painting, mark inspection to the vehicle number are used to display the results. Color extraction algorithm using RGB color model, using MATLAB simulation )

该源代码是粗糙集属性约简，适用环境为matlab，属于常规属性约简(The source code is rough set attribute reduction, for the environment for matlab, part of the regular attribute reduction)

Image processing codes

dBUG源代码 dBUG源代码 dBUG源代码 dBUG源代码(dBUG source code dBUG source code dBUG source code)

ests for KeyGenerator constructor and methods.

针对实际工业生产中常见的多输入多输出时滞过程, 构造多变量Smith预估控制结构, 提出基于对象模 型伴随矩阵的解耦器设计方法. 通过对解耦后对象的幅频和相频特性分析, 获得对象的简化一阶数学模型. 根 据Smith预估控制结构闭环特征方程的特点, 利用Butterworth滤波器极点配置的原理, 对解耦后的多变量时滞过程 设计PI控制器. 结合实际过程中常见的不确定性, 分析了控制系统保证鲁棒稳定性的充要条件. 最后以实例验证了 本文所提方法的优越性.(The decoupling Smith control method is presented for multi-input-multi-output system with time-delays which are often encountered in practical engineering. A new method for designing the decoupler based on the adjoint matrix of the multivariable system model with time-delays is proposed. By analyzing the amplitude-frequency and phasefrequency characteristics of the decoupled model, the decoupled model is reduced to a first-order model with time-delay. According to the closed-loop characteristic equation of Smith predictor structure, a PI controller is developed by using the principle of pole assignment for Butterworth filter. Sufficient and necessary conditions for robust stability are derived for adaptive and multiplicative uncertainties commonly occurred in practice. Simulation results show the superiority of the proposed method.)

Clustering 和 SVM 结合的预测模型算法。聚类采用k-means方法，SVM采用lib-svm工具箱。(kMeans and SVM(support vector machine) prediction model is provided.)