61549826Hierarchical

模糊自整定PID控制器设计。 本资料含有详细的PID控制器算法M文件、Simulink模型搭建、模糊控制器设计以及相应的技术文档分析。相信对您一定很有帮助(Fuzzy self-tuning PID controller design. This information contains details of the PID controller algorithm M files, Simulink models to build, fuzzy controller design and analysis of relevant technical documentation. I believe you must be helpful)

说明：  R implementation of a regression method to optimize stock values. The files contain code and two text files with two different examples. Coded using RStudio.

快速扩展随机生成树算法，多机电力系统仿真及其潮流计算，计算十字叉丝的在不同距离的衍射图像。( Rapid expansion of random spanning tree algorithm, Multi-machine power system simulation and flow calculation, Calculation crosshairs diffraction image at different distances.)

将骨头图片进行滤波，增强等等操作，得出理想图像。(Bones picture filtering, to enhance the operation and so on, come to the ideal image.)

To plot a 16-QAM signal constellation with annotations that indicate the mapping integers to constellation points. The code uses the scatterplot function to create the plot and the text function in MATLAB to create the annotations. We follow the following steps for this.

Hand recognition using Keypoint matching algorithm is implemented

该程序是turbo码仿真程序,由12个m文件组成,分别是turbo编码(包括凿孔和非凿孔turbo码生成),译码网格和软判决迭代译码等模块,主程序可以直接运行,也可根据需要修改相应参数(The program is turbo code simulation program, from 12 m paper, namely, turbo coding (including bore and non-bore turbo code generation), decoding grid and soft-decision iterative decoding modules, the main program can direct operation, may also need to be amended in accordance with the corresponding parameters)

Digital image processing for lecture

Guyan法模型减缩,缩减系统治疗刚度矩阵维数，同时保持低阶模态精确性(Guyan condensaton method)

k means techniques de classification non supervisée (clustering) les plus utilisées. Etant donné un entier K, K-means partitionne les données en K groupes, ou "clusters", ou "classes" ne se chevauchant pas. Ce résultat est obtenu en positionnant K "prototypes", ou "centroï des" dans les régions de l espace les plus peuplées. Chaque observation est alors affectée au prototype le plus proche (règle dite "de la Distance Minimale"). Chaque classe contient donc les observations qui sont plus proches d un certain prototype que de tout autre prototype