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随机产生一QPSK调制信号，通过一随机产生的低通滤波器，然后使用LMS算法实现了系统哦你的辨识。(Randomly generate a QPSK modulation signal generated by a random low-pass filter, and then use the LMS algorithm of the system Oh, your identification.)

here is a good code for reay please check it out guys

81 level inverter which uses embedded function block and has the THD around 1 percent

一个等温边界条件下计算墙角内温度场的小程序，用户输入墙角两侧温度，墙体热导率，设定网格尺寸后程序便会自动迭代求解并同时以矩阵和三维图形的形式输出运算结果。(A small program to calculate the temperature field inside the corner under the condition of isothermal boundary is introduced. When users enter the temperature on both sides of the corner, the thermal conductivity of the wall and the size of the mesh, the program will automatically solve the problem and output the results in the form of matrix and three-dimensional graphics.)

在SENSE成像中如何将中间图像转化为最终图像，就要用到这个程序(Using specfied sampling vector to generate a 2D aliasing matrix. The sampling vector is a vector of n-entries of either 0 or 1, where 0 indicates no k-space line acquisition and 1 indicates k-space line is acquired in the accelerated scan. For example, a sampling vector of [0 1 0 1 0 1 0 1 0 1] indicate the 2-fold acceleration with 8 phase encoding lines. The aliasing matrix is calculated based on Fourier imaging)

用db5小波分解嗲能质量信号 并低频部分高频进行重构 最后给出图像(Db5 can whine with the quality of the signal wavelet decomposition and reconstruction low-frequency part of the high-frequency image is given)

In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.

Algorithms for Digital Image Steganography via Statistical Restoration

用matlab实现了粒子群优化算法，算法可以自己设置初始化参数。(Particle swarm optimization algorithm is implemented by MATLAB.)

混沌函数，很好用的哈，大家试一试哈，真的呀(failed to translate)