python入门6-10章节练习源代码

说明：  《MATLAB R2016a数字图像处理34例》张德丰 著(34 cases of MATLAB r2016a digital image processing by Zhang Defeng)

说明：  展示公司官网页，招聘信息，公司产品，地址等(Display company official website, recruitment information, company products, address, etc.)

说明：  C#高级编程(中文第七版)是一本非常具有实用性的书籍。(C # Advanced Programming (Chinese 7th Edition))

gabor提取纹理特征，k-means方法无监督聚类进行图像分割(extract texture feature, cluster by k-means)

设置有四个信标节点发射固定频率的声波信号，在另一个z轴平面有一移动节点以一定速度移动(Set up four beacon nodes at a fixed frequency acoustic signal, in another z axis plane one mobile node move at a certain speed)

机器学习第二版书籍源码，文件较大，分章节上传(This is the code repository for Python Machine Learning - Second Edition, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.)

(1) 设计一个整数的补码类，有利于任意长整数的补码表示 及其运算； (2) 整数以十进制输入，对输入的数据要进行合法性检查； (3) 实现十进制数的补码转换、补码输出（输出格式为：每 8bit 一组，各组间以空格隔开）。 ((1) u8BBE u8BA1 u4E00 u4E2 u4E2 u657 u6570 u7654 u8865 u7801 u7C7B uFF0C u6709 u5229 u4E8E u4EFB u610F u657 U793A u53A u5136 u8F3 u8F3 u8F0 U5408 u6602 u03123 u03121 u8R03 U8F93 u51FA u683C u5F0F u4E3A uFF1A u6BCF 8bit u4E00 u7EC4 uFF0C u5404 u7EC4 u952F0 u4EE5 u7A7A u683C u9694 u5F00 uFF09 u3002)

，建立车体6个自由度加上前轮转向系统1个 自由度的汽车数学模型；该汽车数学模型不需引入很多的人为假设；可以实现给定汽车前轮转角，也可以不给定前轮 转角；不依赖需要复杂测定的侧向力函数及相关模型参数；考虑了轮胎的滚动特性(, 6 degree of freedom body set up with front-wheel steering system a degree of freedom mathematical model of the vehicle mathematical model of the motor vehicle without the introduction of the assumption that a lot of man-made can achieve a given vehicle' s front wheel angle, it may not give pre-set rotation angle do not rely on the complexity of the determination of the required lateral force function and the related model parameters taking into account characteristics of the tire rolling)

说明：  随机森林算法与 Bagging 算法类似，均是基于 Bootstrap 方法重采样，产生多个训练集。不同的是，随机森林算法在构建决策树的时候，采用了随机选取分裂属性集的方法 本程序中，将乳腺肿瘤病灶组织的细胞核显微图像的 10 个量化特征作为模型的输入，良性乳腺肿瘤和恶性乳腺肿瘤作为模型的输出。用训练集数据进行随机森林分类器的创建，然后对测试集数据进行仿真测试，最后对测试结果进行分析。(Similar to bagging algorithm, random forest algorithm is based on bootstrap resampling to generate multiple training sets. The difference is that the random forest algorithm uses the method of randomly selecting the split attribute set when constructing the decision tree In this program, 10 quantitative features of nuclear microscopic image of breast tumor tissue are taken as the input of the model, and the benign and malignant breast tumor are taken as the output of the model. The training set data is used to create the random forest classifier, then the test set data is simulated and the test results are analyzed.)

平衡截断算法 用于计算模型降阶过程的计算方法，属于控制论范畴(truncation balanced method)