CHI2TEST：单样本 Pearson 卡方拟合优度假设检验。 H=CHI2TEST(X,ALPHA) 执行 Pearson 卡方检验的特殊情况，以确定复合正态性 PDF 的原假设是否是关于具有所需显着性水平 ALPHA 的随机样本 X 的总体分布的合理假设。 H表示根据条件语句的MATLAB规则进行假设检验的结果： H=1 => 不要在显着性水平 ALPHA 拒绝原假设。 H=0 => 在显着性水平 ALPHA 拒绝原假设。 在这种特殊情况下，卡方假设和检验统计量是： 零假设：X 是正态的，均值和方差未知。 替代假设：X 不正常。 随机样本 X 按其估计均值移动，并通过其归一化估计标准差。 选择假定正态分布的测试箱 XP [-inf, -1.6:0.4:1.6, inf] 以避免统计不足。 设 E(x) 是 X 根据正态分布落入 XP 的预期频率，O(x) 是观察到的频率。

Matlab 文件在动态系统的反馈控制，第 7 版，Pearson，2015 年，GF Franklin、JD Powell、A. Emami-Naeini 中创建图形

Details Title: Digital Image Processing, 4th Edition Author: Rafael C. Gonzalez, Richard E. Woods Length: 1192 pages Edition: 4 Language: English Publisher: Pearson Publication Date: 2017-03-30 ISBN-10: 0133356728 ISBN-13: 9780133356724 Sales Rank: #680902 (See Top 100 Books) Categories Computers & Technology Engineering & Transportation Engineering Textbooks Description Introduce your students to image processing with the industry’s most prized text For 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer programming. As in all earlier editions, the focus of this edition of the book is on fundamentals. The 4th Edition, which celebrates the book’s 40th anniversary, is based on an extensive survey of faculty, students, and independent readers in 150 institutions from 30 countries. Their feedback led to expanded or new coverage of topics such as deep learning and deep neural networks, including convolutional neural nets, the scale-invariant feature transform (SIFT), maximally-stable extremal regions (MSERs), graph cuts, k-means clustering and superpixels, active contours (snakes and level sets), and exact histogram matching. ?Major improvements were made in reorganizing the material on image transforms into a more cohesive presentation, and in the discussion of spatial kernels and spatial filtering. ?Major revisions and additions were made to examples and homework exercises throughout the book. For the first time, we added MATLAB projects at the end of every chapter, and compiled support packages for you and your teacher containing, solutions, image databases, and sample code. The support materials for this title can be found at www.ImageProcessingPlace.com

推荐系统 利用MovieLens数据，Pearson相似度，分别基于User和Item构建一个简单的kNN推荐系统，并进行RMSE评价

1、数据集预览 原创文章 113获赞 137访问量 7万+ 关注 私信 展开阅读全文 作者：Vivid-victory

推荐系统 使用Pearson和KNN的推荐系统

Pearson相关系数实现代码

空气污染是目前的热点问题,导致主要污染物浓度变化的原因错综复杂,影响程度大小也各不相同。统计北京和广州两个城市的2016年5月份的污染物浓度和气象情况,对各个气象因子与污染物浓度进行相关性分析,得到两个变量间的Pearson系数并进行了比较。找出了两城市的主要污染物并总结两个城市的空气污染物变化情况,分析得出了大气影响因子受不同污染物的影响关系。

皮尔逊相关系数 皮尔逊相关性和每个vox相关性。

实现了计算Pearson相关，内含一个实例，详细的使用说明，和Pearson相关基础知识的介绍PPT