Quantum Radar[Marco Lanzagorta(2012)141s]

说明：  在Linux系统下读取惯导数据，输出姿态角（横滚角、俯仰角、偏航角）(Reading inertial navigation data under Linux system, output attitude angle (roll angle, pitch angle, yaw angle))

前方交会摄影测量matlab编码。其中xy是相片坐标，XYZ是地理坐标，ms是摄影比例尺(Forward rendezvous photogrammetry matlab coding)

TeeChart Pro是一个强大的VCL图表组件，支持上百种2D和3D图表风格，并提供40多个数学和统计函数、无限制的轴和22个调色板(TeeChart Pro is a powerful VCL graphics component that supports hundreds of 2D and 3D graphics styles and provides more than 40 mathematical and statistical functions, unlimited axes and 22 palettes.)

说明：  在葡萄酒制造业中，对于葡萄酒的分类具有很大意义，因为这涉及到不同种类的葡萄酒的存放以及出售价格，采用神经网络做为分类器可以有效预测相关葡萄酒的种类，从UCI数据库中得到wine数据记录的是在意大利某一地区同一区域上三种不同品种的葡萄酒的化学成分分析，数据里含有178个样本分别属于三个类别(类别标签已给)，每个样本含有13个特征分量(化学成分)，将这178个样本70%做为训练样本，另30%做为测试样本，用训练样本对神经网络分类器进行训练，用得到的模型对测试样本的进行分类标签预测。(In the wine manufacturing industry, classification of wine is of great significance, because it involves the storage and selling price of different kinds of wine. Using neural network as classifier can effectively predict the types of related wine. The wine data recorded from UCI database is the chemical composition of three different kinds of wine in the same region of Italy According to the analysis, 178 samples in the data belong to three categories (the category label has been given). Each sample contains 13 characteristic components (chemical components). 70% of the 178 samples are used as training samples, and 30% are used as test samples. The training samples are used to train the neural network classifier, and the model is used to predict the classification label of the test samples.)

说明：  EMD改进版CEEMDAN，具体详见百度(CEEMDAN algorithm further reduces the modal effect by adding adaptive noise and has better convergence good)

说明：  我的世界所有的版本的材质包！可以看到矿物！挖矿必备！(All versions of the material package in my world! You can see minerals! Mining is essential!)

JAVA游戏改中文名!不妨试一试！方便安装后查阅！-JAVA game to change the Chinese name! May wish to try it! Easy installation inspection!

PhaseU，一种 实时LOS识别方案，既适用于静态也适用 商用WiFi基础设施的移动场景。 各种室内场景的实验结果表明了这一点 PhaseU始终优于以前的方法，实现了总体LOS和NLOS检测率为94.35％和 静态情况下为94.19％，移动电话均高于80％ 上下文。 此外，PhaseU实现了实时功能 连接AP的毫秒级延迟和1秒延迟 对于未连接的AP，这远远超出现有方法(PhaseU, a real-time LOS identification scheme that works in both static and mobile scenarios on commodity WiFi infrastructure. Experimental results in various indoor scenarios demonstrate that PhaseU consistently outperforms previous approaches, achieving overall LOS and NLOS detection rates of 94.35% and 94.19% in static cases and both higher than 80% in mobile contexts. Furthermore, PhaseU achieves real-time capability with millisecond-level delay for a connected AP and 1-second delay for unconnected APs, which is far beyond existing approaches)

VxWorks6.9 官方文档 BSP开发 vxworks_b developers_guide_6.9(VxWorks official documentation BSP developed vxworks_b developers_guide_6.9)

代码计算幅相误差对MUSIC算法的影响，一共两个.m文件(1.array_am_pha_error_on_music.m 2.error_matrix)