pca

短时傅立叶变换测频，可对复信号处理。界面设计好，用户交互方式编程。(STFT frequency measurement can be complex signal processing. Interface design, the user interactively programming.)

说明：  MATLAB程序（附图像），利用彩色AGV对路径进行识别。(MATLAB (AP like), using color AGV right path for identification.)

Matlab code for image processing first formation for user matlabe programing

说明：  跳频系统的同步simulink仿真（R2010b）(Synchronous hopping simulink simulation system)

Induction machine MAT/Simulink

MATLAB structures provide a way to collect arrays of different types and sizes in a single array. The following codes show how this can be made for problem1.m. One of the most interesting features is that the argument passing to functions is simplified. MATLAB codes for Finite Element Analysis problem1.m antonio ferreira 2008

将idNO类中序列相差2以内的子序列进行连接，用于交流留的数据处理(Conecting the subsequences which are next to others (less than 2). This is used for data processing of transpotation flow)

\this file contains the matlab file for radon function with its c file. to run on matlab compile the file using c++ compiler to convert c file into mex file.

波达方向（DOA） 估计的基本问题就是确定同时处在空间某一区 域多个感兴趣的信号的空间位置(即多个信号到达阵列参考阵元的方 向角)。最早的也是最经典的超分辨率(DOA)估计算法是著名的多信号 分类（Multiple Signal Classification） 法,简称 MUSIC 算法,它是 一类经典的基于特征结构分析的空间谱估计方法。该算法利用了信号 子空间和噪声子空间的正交性,构造空间谱函数,通过谱峰搜索,检测 信号的 DOA。(The basic problem of DOA estimation is to determine the simultaneous location in a certain region of space. Spatial position of multiple interested signals in the domain (i.e. the direction of multiple signals reaching the array reference elements) Directional angle). The earliest and most classical super-resolution (DOA) estimation algorithm is the well-known multi-signal.Multiple Signal Classification, referred to as MUSIC algorithm, is A classical spatial spectrum estimation method based on eigenstructure analysis. The algorithm utilizes signals. The orthogonality of subspace and noise subspace, the construction of spatial spectral function, through peak search, detection DOA of signal.)

运用主成分分析法和K均值聚类法来进行SAR影像变化检测(SAR image change detection using principal component analysis and K-means clustering)