knn(带数据)

说明：  U盘读写模块，实现电脑与U盘自动连接，发送，传输数据(U-reader module, computerization and U disk automatically, sending, transmission of data)

说明：  实现UWB仿真，用于实现自动追踪定位，即卡尔曼滤波算法(Implement UWB simulation for automatic tracking and positioning, namely Kalman filter algorithm)

Sellmeier index calculation

说明：  信号处理综合建模仿真 1、 楼体模型的建立。 2、 实际环境干扰（如树木遮挡、环境噪声、系统内部噪声等）的加入。 3、 信号的反射与穿透衰减的考虑。 4、 天线扫描方式的确定。 5、 空间-SNR三维图像的绘制。(Integrated Modeling and Simulation of Signal Processing)

航空航天通信技术一般采用模拟通信的频率调制和数字通信的移相键控调制方法。这有利于充分应用信道带宽和能源。频率调制是在一定程度上改变载波或副载波的频率来传输信息的调制方法。移相键控调制是利用载波或副载波的相位跳变来传输信息的调制方法。移相键控又分二相移相键控、四相移相键控和多相移相键控，其中以四相移相键控和八相移相键控调制方法的效率较高(Aerospace communications technology commonly used analog communication of frequency modulation and the digital communication phase shift keying modulation method. This is helpful for making full use of channel bandwidth and energy. Frequency modulation is changed to some extent carrier or subcarrier frequency to transmit information modulation method. Phase shift keying modulation is the use of carrier or subcarrier phase jump to transmit information modulation method. Phase shift keying and binary phase shift keying, four phase shift keying and multiple phase shift keying, of which four phase shift keying and eight phase shift keying modulation method of high efficiency )

说明：  使用wifi信号进行人体定位追踪，里面有AOA和TOF的计算能够准确计算人体位置(Using WiFi signal to locate and track human body.The calculation with AOA and TOF can accurately calculate the position of human body)

simulink搭建的卫星姿态动力学仿真，参考书籍是章仁为的卫星鬼道姿态动力学仿真，想学对卫星姿态有兴趣的同学强烈推荐，(simulink to build the satellite attitude dynamics simulation, reference books is Zhang Ren ghosts satellite attitude dynamics simulation, I wanted to learn for students interested in satellite attitude is strongly recommended,)

Design of Low Complexity OFDM Schemes and Position Location Algorithm for ... By Syed Faisal Ali Shah PrecodING OFDM System THESIS Go

一个关于IEEE802.15.4a信道原理的matlab编码(A on IEEE802.15.4a channel matlab coding)

说明：  第一次作业_基于分类算法的雷达状态识别 对于本数据集中的雷达状态识别，数据降维前使用朴素贝叶斯、支持向量机、神经网络的分类算法对于识别的准确率无太大影响；数据降维后使用神经网络算法最优，支持向量机算法其次，朴素贝叶斯算法较差。此外，训练样本越多，分类准确率有小幅度提高。(First Operation Radar State Recognition Based on Classification Algorithms For radar state recognition in this data set, the classification algorithm of Naive Bayesian, Support Vector Machine and Neural Network before data dimension reduction has little effect on the accuracy of recognition; Neural Network algorithm is the best after data dimension reduction, Support Vector Machine algorithm is the second, Naive Bayesian algorithm is the worst. In addition, the more training samples, the smaller the classification accuracy.)