Matlab7GUI

使用MATLAB软件工具来解决他和著名的TSP(Using MATLAB software tools to solve the TSP famous)

预处理的源定位 ------------------------------------- 各种脚本用于处理源定位中使用的时间数据。 Time2Frames.m mutilchannel时间数据转换为频谱帧 Time2TF.m 时间数据转换为相对传递函数的帧到通道1。 Frames2R.m 频谱帧转换为（freqeuncy而定）的协方差矩阵。 R2C.m 转换协方差矩阵噪声子空间（用于音乐）。 Clean_Source.m 从协方差矩阵中删除第n个最强的源极（S）。(Preprocessing for source localization ------------------------------------- Various scripts for processing time data to be used in source localization. Time2Frames.m Converts mutilchannel time data to spectral frames Time2TF.m Converts time data to frames of transfer function relative to channel 1. Frames2R.m Converts spectral frames to (freqeuncy dependent) covariance matrices. R2C.m Converts covariance matrices to noise subspace (for MUSIC). Clean_Source.m Removes the nth strongest source(s) from the covariance matrix.)

用matlab模拟二维海面的程序，第一步求出海面的公式，第二步利用求出的公式画出海面(Matlab simulation of two-dimensional surface using the procedure, the first step to derive the formula for the sea, and the second step to derive the formula to use to draw the sea)

说明：  灰色GM(1,1)和DGM源代码，功能齐全，各种显示内容均添加(Grey GM (1,1) source code, complete functions, various displays are added)

这个算法是matlab里面压缩感知OMP算法的程序，对一个信号进行采样。(This algorithm is inside compressed sensing OMP algorithm matlab program, a signal is sampled.)

qpsk调制程序，通过仿真，用matlab编写的(qpsk modulation process, through simulation, written with matlab)

node 例子，帮助初学者了解使用 node 环境编程(node test model)

很快的求出各点对之间的最短距离，并且记录路径。(Quickly find out the point to the shortest distance between, and record path.)

短时傅里叶变换可以用差分模式来实现，对书上的运算式做了稍许的改变。改变-计算差分序列的第一列数据时用的是第一列的元素减去当前行的最后一列元素。原算法中采用的是第一列元素减去下一行第二列元素。原算法加窗之后结果比较好，不加窗时结果误差很大，而改变之后的算法不加窗效果依然很好。(Short time Fourier transform can be used to achieve the differential mode of expression on the book made a slight change. Change- calculating the difference sequence of the data with the first column is the first column of the matrix by subtracting the current element in the last column of row. Is used in the original algorithm subtracts the elements of the first column of the next row and the second column elements. After the results of the original algorithm windowed better, when the results window without great error, and after changing algorithms no window effect is still very good.)

扩展卡尔曼在定位中的一个例子,在滤波分析中很实用(Extended Kalman positioning an example, very useful in filtering analysis)