Inc_cirlar

Economic dispatch by simulating anneling

说明：  一个完整的OFDM通信系统，采用16QAM调制，设置不同的信噪比，得到误码率(A complete OFDM communication system adopts 16QAM modulation, sets different SNR, and gets bit error rate)

这个是一份很有用的ECG信号处理原数据，是从国外一个老师那里要来的，可以用来做一位信号去噪处理。(this is a very useful source data for ECG signals. I obtained this data from a foreign professor.This data can be used for 1-D signal denosing,)

附带四种SVM工具箱的分类以及回归算法源代码(Four SVM classification and regression algorithm toolbox)

内模控制实现程序 基于MATLAB2010a环境下实现(Implement procedures based on internal model control environment to achieve MATLAB2010a)

说明：  配电网规划必须满足辐射性和连通性，配电网扩展规划问题随机产生的初始群体中往往存在大量不可行解，采用根节点融合法可确保方案的可行性。(Distribution network planning must meet radiation and connectivity, distribution network expansion planning problem with randomly generated initial population there is often a large number of infeasible solutions, use of root fusion method to ensure feasibility.)

Learning automata based classifier

说明：  mylsb.m是个非常完整的LSB密写源码并且密写和提取都在里面，图片我没上传，你只需要添加一个图片文件就可以了，记住图片必须是灰度图片，如果是RGB，我转换的代码也在里面很有意思哦。weipingmian.m是个提取图像位平面的程序，图片也是需要你自己加载，最后一个就是8*8块的图像DCT变换。(mylsb.m is a very complete source of LSB Steganography Steganography and extraction, and are on the inside, I did not upload pictures, you only need to add a picture file on it, remember the image must be a grayscale image, if it is RGB, I converted the code is also very interesting inside Oh. weipingmian.m is a program to extract bit-plane images, pictures, you also need to load the last one is 8* 8 DCT transformed image.)

一种基于最小熵反褶积( ]8+83)3 6+D*(A4 Q20(+W(-)D8(+，]6Q) 的滚动轴承故障特征提取方法: 在利用 /X 模型去除齿轮啮合产生的确定性信号的基础上，对保留信号进行最小熵反褶积，增强冲击信号"该方法避免了传统轴承故障诊断方法中带通滤波器设计的难题，实车测试表明: 与共振解调技术相比，该方法提取的滚动轴承故障特征更加明显，更适合于工程应用"(Based on minimum entropy deconvolution (] 8+83) 3 6+D* (A4 Q20 (+W (-) D8 (+,] 6Q)' s fault feature extraction method: using/X model to remove the uncertainty generated signal gear on the basis of the retention signal minimum entropy deconvolution, and enhance the impact of signal " This method avoids the problems of traditional bearing fault diagnosis method of the bandpass filter design, real vehicle test showed that: compared with the resonance demodulation technology, which fault feature extraction method is more obvious, more suitable for engineering applications. " )

code for watching matlab rbf neural net