Polygons-Intersection

<数理统计与MATLAB工程数据分析> 清华大学出版社 随书代码(<Mathematical statistics and MATLAB data analysis projects> Tsinghua University Press with the code book)

说明：  MIMO注水原理的简单运用,有助于理解SVD分解,注水算法,不同发送天线上如何进行功率分配(MIMO injection principle of a simple application helps to understand SVD decomposition algorithm injection, Send different antennas on how power distribution)

本实验的内容是无线楼宇数据传输仿真，分析915M的楼宇通信特性，建立楼宇数据通信系统的仿真模型，采用无线收发芯片NRF905，依据其性能参数来判断楼宇内两点能否进行数据传输(the contents of this experiment is building wireless data transmission simulation, analysis 915M communications characteristics of the buildings, establishing building data communications system simulation models, the use of wireless transceiver chip NRF905. based on its performance parameters to judge whether two buildings for data transmission)

Implementation of Particle Swarm Optimization Algorithm for solving continuous problem.

1. 按照式计算相似性矩阵 2. 排除自身的相似度 3. 按照式计算归一化矩阵 4. 按照式计算归一化拉普拉斯图矩阵L 5. 计算L的特征向量，将前个特征值最大的向量按列放置成一个矩阵，即依次为前个特征值最大的特征向量 6. 归一化X形成矩阵Y 7. 对矩阵Y按每行为一个数据点，进行k-means聚类，第行所属的类就是原来所属的类。(1. similarity matrix based on formula computation 2. rule out your own similarity. 3. normalized matrix based on formula computation 4. normalized formula Laplasse matrix L according to formula. 5. Calculate the eigenvectors of L. Place the vectors with the largest eigenvalues in columns into a matrix, that is, the eigenvectors with the largest eigenvalues in turn. 6. normalized X formation matrix Y 7. K-means clustering is applied to matrix Y according to one data point per behavior. The first row belongs to the original class.)

matlab读取ers sar 数据 matlab读取ers sar 数据 matlab读取ers sar 数据 asar 数据(read ers sar and asar data)

利用matlab软件编写模糊聚类算法，将脑叶图片不同像素点分离(Software written using matlab fuzzy clustering algorithm, the lobe separation of different pixel images)

小型风电系统用到的BUCK电路SIMULINK模型，已经MPP模型，利用MPPT产生的PWM，控制BUCK电路，实现最大功率跟踪(Small wind power systems used BUCK circuit SIMULINK model has the MPP model, produced by MPPT PWM control BUCK circuit, to achieve maximum power tracking)

利用PSO优化SVM中的c和g c1:初始为1.5,pso参数局部搜索能力 c2:初始为1.7,pso参数全局搜索能力 maxgen:初始为200,最大进化数量 sizepop:初始为20,种群最大数量(Support Vector Machine Optimized by Particle Swarm Optimization )

remove noise from multiple noisy images