chenxu

能够实现对三维点云数据的中值滤波、均值滤波、以及最小二乘滤波(Able to achieve a three-dimensional point cloud data, median filtering, mean filtering, and least squares filtering)

仿真图是速度、距离、幅度三维图像，ICA（主分量分析）算法和程序，利用最小二乘算法实现对三维平面的拟合。( FIG simulation speed, distance, amplitude three-dimensional image, ICA (Principal Component Analysis) algorithm and procedures, Least-squares algorithm to fit a three-dimensional plane.)

fast k-means algorithm

采用logistic构造的混沌模型，可以产生混沌序列，简单修改参数后可以产生任意区间的混沌序列程序(using logistic structure of chaotic model can produce chaotic sequence, After the simple parameter changes can have arbitrary interval of chaotic sequence procedures)

the most chatoc attractors for encryption and other application

有限元6面体8节点等参元的单元刚度阵计算函数(failed to translate)

simulink的入门教程，老师上课讲的课件，较易懂，适用于初学者(simulink introductory tutorial, the teacher talked about class courseware, more easy to understand for beginners)

基于改进的PI模型对非线性曲线进行拟合，二次寻优算法进行参数辨识，用逆模型前馈补偿(Based on the improved PI model, the nonlinear curve is fitted, and the second optimization algorithm is used to identify the parameters, and the inverse model feedforward compensation is used.)

说明：  选择“BreastCancer”数据集，使用支持向量机(SVM)对其进行分类。作为对比，第一次对特征集直接进行支持向量机分类，第二次对特征集进行主成分分析法的特征提取后，再对特征提取后的特征集进行支持向量机分类。并且对比和分析了两次分类的结果。(The BreastCancer data set is selected and classified by Support Vector Machine (SVM). For comparison, the first time the feature set is classified directly by support vector machine, the second time the feature set is extracted by principal component analysis, and then the feature set is classified by support vector machine. The results of the two classifications are compared and analyzed.)

基于matlab环境下的 绘制彩色玫瑰花的小程序 效果还是不错的 建议大家下载测试(Matlab environment based on the rose colored drawing or a good small program effects suggest that you download the test)