fengsumoxing

说明：  Matlab_FFT方法检测正弦波相位 (Matlab_FFT phase sine wave was detected)

非合作时频分析的文章，是这个方向的重要文献，对学习很有帮助(Time-frequency analysis of non-cooperation of the article, is an important document in this direction, to learn helpful)

基于 Matlab 的锁相环（PLL）模拟代码。(Basic Phase-Locked Loop simulation code in Mtalab)

Data Encryption by Matrix Multiplication We will only use numbers 0 to 26 for the encryptive mathematics operation. Numbers from 1 to 26 are for letters from A to Z and 0 is for all non-letter characters. To minimize usage of numbers, all letters are converted to upper case. The original message is converted to number array according to the ASCII table and minus 64. We partition whole array into blocks of 8 numbers. The last block may be added several zeros. Then multiply each block by the an 8x8 matrix A which is invertible in Z27 to get cipher data. The decryption is the same process except to use its inverse matrix B. For good visual reading, we convert all non-letter characters to under score for the decryption.

小型电网，模拟小型电网做的关于MATLAB的simulink图，适合初学者学习和利用，可以扩充和修改。(Mini-grids, analog mini-grids made ​ ​ on MATLAB simulink diagram, suitable for beginners to learn and use, can be expanded and modified.)

单极性PWM电路的simulink仿真图，包含波形(simulink simulation diagram unipolar PWM circuit includes a waveform)

说明：  m-k趋势检验，做时序趋势变化的方法的源代码(M-k trend test, the source code of the method of temporal trend change)

说明：  一种混合贪婪随机自适应搜索（GRACH）算法，用于解决单车辆段车辆路径问题(a hybrid Greedy Randomized Adaptive Search (GRASP) algorithm that solves a single depot vehicle routing problem)

小波谱分析mallat算法经典程序，用的也是一维信号(small spectral analysis algorithm Mallat classic procedures, as well as the one-dimensional signal)

　k-means 算法接受参数 k ；然后将事先输入的n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。(K-means algorithm accept parameter k Then will the n of prior input data object is divided into k clustering to make won clustering meet: the same clustering the object in the similarity is higher And different clustering the object in the smaller similarity. Clustering similarity is using the cluster of the object in the mean gained a "center object" (the center of gravity) to calculate. )