Otsu-segmentation-method-for-check

使用MATLAB编写的角点检测源代码，并附有用于检测算法的图形(The use of MATLAB prepared corner detection source code, together with the graphics for the detection algorithm)

说明：  bp是MATLAB应用中的预测算法，含有例题(BP and MATLAB)

用MATLAB实现的车牌分割程序，喜欢的可以下载(Implemented using MATLAB license plate segmentation procedure)

在快速傅里叶变换大的基础上以对信号进行短时分析，能画出三维瀑布图。(In the fast Fourier transform big on the basis of the signal is short analysis, can draw 3 d waterfall diagram )

现有的几个网络拓扑随机发生器，其实很难生成理想的网络拓扑结构，其主要原因在于很难控制节点的疏密和间距。我们提出来的这个改进算法，在随机抛撒节点的时候使用了K均值聚类，由本算法作为网络拓扑发生器，网络节点分布均匀且疏密得当，边的分布也比较均衡(The few existing random network topology generator, is in fact very difficult to generate the desired network topology, the main reason it is difficult to control the node density and spacing. We put forward the improved algorithm, throw in random nodes when using the K-means clustering, by the algorithm as a network topology generator, network nodes and spacing evenly distributed properly, the edge of a more balanced distribution of)

说明：  matlab通过OLEDB方式读取数据库中的数据（Access版）(matlab way through the OLEDB to read data in the database (Access version))

针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。 (For the signal adaptive the chirplet decomposition of unknown parameters to achieve difficult to literature [1] proposed a new fast algorithm for chirplet decomposition. The algorithm makes use of the secondary phase of the calculated signal function, the conclusion focused on energy distribution curve to tune the frequency of the signal by the peak detection chirplet tune frequency, time center and amplitude estimates then by solving chirp technology to obtain the initial frequency and width is estimated that the simulation results demonstrate the effectiveness of the proposed algorithm.)

this code is to learn about MATLAB

利用贝叶斯实现的分类器小程序，显示出按照最小风险和最小误差分类的结果(Bayesian classifier implemented using a small program to show in accordance with the minimum risk and minimum error classification results)

通过MATLAB软件所建立的CRH2动车的模型。(Established through MATLAB software model CRH2 EMU.)