改进MFO算法3

说明：  利用matlab进行图像的重建和修复，利用福利也计算和拉普拉斯变化得到的.(Use of matlab for image reconstruction and restoration, use of welfare also changes the calculation and Laplace received.)

It& is& a& Programming& Language& for& Scientific& Computing&   It&is&a&Numerical&Computing&Environment&where&you& can&test&or&implement&algorithms&   It&is&a&Software&which&runs&on&Windows/Mac&OS/Linux

cdma matlab code full one

这是一个开机自启的控制台应用程序，实在没什么东西拿的出手，但是想看看别人的东西，所以就把这个上载了。大家感兴趣的话可以找我帮忙把他可视化(This is a boot from Kai console application, there really is something to take the shot, but would like to see other people' s stuff, so put this uploaded. We are interested in, then you can ask me for help visualize him)

灰色预测方法的特点表现在：首先是它把离散数据视为连续变量在其变化过程中所取的离散值，从而可利用微分方程式处理数据；而不直接使用原始数据而是由它产生累加生成数，对生成数列使用微分方程模型。这样，可以抵消大部分随机误差，显示出规律性。(The characteristics of the grey prediction method are as follows: First, it regards the discrete data as the discrete value of the continuous variable in its change process, so that the differential equation can be used to process the data; instead of using the original data directly, it generates the cumulative generation. Number, using a differential equation model for generating a series. In this way, most of the random errors can be offset, showing regularity.)

说明：  sdif算法，matlab代码，注释乱码，介意慎点(SDIFsoftware matlab please download)

Solves the Generalized Indicator Function eigenvalue problem

核查的关键在于对核材料属性准确、有效地识别[1][2]。利用252Cf作为随机脉冲中子源，对其入射核材料所产生的诱发裂变中子脉冲信号进行采集、处理和分析，得到自相关、互相关、自/互功率谱、功率谱密度比等一系列参数，从而反演核材料内部的反应性的情况，便可用于分析和识别核材料，其基本原理就是252Cf中子源驱动噪声分析测量法[(The result shows that the trained Elman neural network is able to identify the characteristics of correlation function, to distinguish different concentrations, and the average recognition rate reaches 90 , with high robustness.)

WSN中节点确定性部署算法代码，通过MATLAB运行，可以实现(WSN node deterministic deployment algorithm code, through the MATLAB operation, can be achieved)

支持向量机的学习，简单但实用，推荐给各位哦(Studying supporting vector machine, is simple but pragmatic, recommendation is softly chanted by everybody)