PCA

《从零开始学爬虫》的配套资料（PPT和源码）("Learning Reptiles from Zero" (PPT and Source))

说明：  一种信号的处理方法，用于非平稳的信号处理(A signal processing method for nonstationary signal processing)

说明：  处理ipix官网下载的雷达原始数据，将方位角以及俯仰角进行处理(Processing radar raw data downloaded from IPIX official website)

说明：  利用python进行数据分析，英文书籍，从pandas库的数据分析工具开始利用高性能工具对数据进行加载、清理、转换、合并以及重塑；利用matpIotlib创建散点图以及静态或交互式的可视化结果；利用pandas的groupby功能对数据集进行切片、切块和汇总操作；处理各种各样的时间序列数据。(Starting from the data analysis tools of pandas database, high performance tools are used to load, clean, transform, merge and remodel data; scatter plots and static or interactive visualization results are created by matpIotlib; data sets are sliced, sliced and aggregated by pandas group by function; and various operations are processed. Time series data.)

说明：  从数据库获取车辆在一段时间内的所有行驶记录的相关数据，确定所需数据为GPS经纬度坐标和驾驶时长等，QB模型采用MDF的思想,其基本思想为:通过平均直接翻转距离函数定义两条轨迹之间的距离，两条轨迹需要具有相同的经纬度点数，具有相同点数的轨迹最大的优点是对轨迹距离成对计算，且相同轨迹之间具有更高的分辨率，对于轨迹聚类的结果有一定的优化。(Retrieved from the database cars all over a period of time, record the related data, determine the required data for the GPS latitude and longitude coordinates, and the driving time, QB model by adopting the idea of MDF, its basic idea is: flip directly by the average distance function definition of the distance between two trajectories, two tracks will have the same latitude and longitude points, and has the biggest advantages of the same points of trajectory track distance calculation in pairs, and has higher resolution, between the same trajectory for trajectory clustering results have certain optimization.)

说明：  用python 做的网络数据爬虫，爬取淘宝数据，并分析。(Use Python to do the network data crawler, crawl the Taobao data, and analyze.)

遗传算法优化小波神经网络的源程序 1 构造的非线性函数 位于nninit_test m 2 直接用WNN逼近非线性 Wnn_test()

说明：  用matlab 实现了kmeans算法还附有评价指标计算(Matlab to achieve kmeans algorithm also attached to the evaluation index calculation)

说明：  内附源数据、代码及word。代码包括：平稳性检验、协整检验、滞后阶数的确定、VAR 模型的拟合、脉冲响应分析、VAR 模型的预测(Stationarity test, co integration test, determination of lag order, VAR model fitting, impulse response analysis, VAR model prediction)

常用数值算法源码，包括二分法、复化辛卜生公式、改进欧拉法、高斯-赛德尔迭代法、拉格郎日插值多项式、列主元高斯消去法、龙贝格算法、龙格-库塔算法、幂法、牛顿迭代法、牛顿值多项式、四阶阿当姆斯预测-校正公式、雅可比迭代法、自适应梯形公式（变步长）、最小二乘法 个人由于需要编写，完全可用(Common numerical algorithm source code, including dichotomy, complex Simpson formula, improved Euler method, Gauss-Seidel iteration method, Lagrange interpolation polynomial, column principal element Gauss elimination method, Runberg algorithm, Runge-Kutta algorithm, power method, Newton iteration method, Newton value polynomial, fourth-order Adams prediction-correction formula, Jacobi iteration method, adaptive ladder formula (variable) Step Length and Least Square Method Individuals are fully available because they need to write)