BLDC-simulator

用于现代信号分析与处理课程，正交变换、K-L变换与离散余弦变换。(For modern signal analysis and processing programs, orthogonal transform, KL transform and discrete cosine transform.)

该法是经过改进的基于象素匹配的方法并且还含有图片,对进行景象匹配的朋友有所帮助(The Act are improved pixel-based matching method and also contains a picture of the scene matching to help a friend)

差分方程的蛛网模型，matlab的小例题，方便易懂，解释合理。(Cobweb model of the differential equation matlab example, convenient and easy to understand, explain and reasonable.)

本课题研制了一种宽频带的数字锁相放大器，可以完成自动增益和相位 可调整，最长积分时间为100s，适合于频率从10Hz到10kHz，幅值从100nV 到10mV的微弱正弦信号检测。测量结果表明，当采样点数N大于8192时， (This project developed a wideband digital lock-in amplifier, can be completed automatically adjustable gain and phase, the longest integration time of 100s, suitable for the frequency range from 10Hz to 10kHz, amplitude from 100nV to 10mV of weak sine signal detection. The measurement results show that, when the sampling point number N is greater than 8192 hours,)

说明：  matlab 直接序列扩频中对于高斯白噪声的抗干扰仿真仿真程序(matlab in direct sequence spread spectrum interference for the simulation of Gaussian white noise simulation program)

C++ Primer Plus, 作者 Stephen Prata 版本6ed, AW, 年份 2012 C++初级学者用书(C++ Primer Plus, Stephen Prata, 6ed, AW, 2012 C++ junior scholars books)

说明：  提取图像的GLCM矩阵，并计算出Haralick建议的14个特征值(Extract images GLCM matrix, and calculate the 14 Haralick features of the proposed values)

三维点云法向量估计综述由于获取方便、表示简单、灵活等优势，点云逐渐成为常用的三维模型表示方法之一。法向量作为点云必不可少的属性 之一，其估计方法在点云处理中具有重要的位置。另一方面，由于点云获取过程中不可避免的噪声、误差和遮挡，点云中通常含 有噪声、外点和空洞，并且部分采样模型如CAD模型，也会存在尖锐特征，这些都给法向量估计提出了挑战。对当前已有的点云 法向量估计算法进行综述，分析其原理及关键技术，着重分析它们在处理噪声、外点和尖锐特征等方面的能力并给出比较，最后 为未来研究提供了一些建议(The three-dimensional point cloud normal vector estimation summarized obtain convenient, represents a simple, flexible, and becoming one of the methods commonly used three-dimensional model represents the point cloud. Normal vector of one of the as point clouds essential attributes, its estimation method has important position in the point cloud processing. On the other hand, the noise is inevitable in the process to obtain because of the point cloud, error and occlusion, point cloud typically contains noise outside point and empty, and part of the sampling model such as CAD models, there will still be sharp features, which gave the normal vector estimated that presents a challenge. Overview of current existing point cloud normal vector estimation algorithm, analysis of the principle and key technologies, and analyzed their ability to deal with the noise, the outer points and sharp features and gives comparison, and finally provide some suggestions for future research)

一种基于边缘特征的二值化算法，效果较好，里面还有ppt，讲解算法的主要思想 还有matlab源码。(based on the characteristics of two marginal value of the algorithm, the result is better and there is also ppt. Algorithm on the main ideas are still Matlab source.)

解非线性方程组的gui程序，选自机械工业出版社出版的《时尚百例丛书》(solving nonlinear equations of gui procedures, industrial machinery from the publishing house "Fashion 100 cases Series")