lls

it is about optimisation with swarm s method

说明：  本算法是基于鸡群优化算法CSO优化SVM，可以大大提高VMD的分类准确率，提高优化时间。(This algorithm is based on CSO to optimize SVM, which can greatly improve the classification accuracy of VMD and improve the optimization time.)

第一步：首先我们需要强大的SNMP信息收集和整理工具，网络中这类工具比较多，如果我们只是监控的话建议使用小巧的monomon即可，当然如果企业内部要自定义建立流量监控站点或服务中心的话可以使用其他支持SNMP的MRTG，PRTG等工具。我们可以到http://monomom.matf.de/download.php地址下载该程序，整个程序只有一个文件(Step one: First of all, we need strong SNMP information to collect and organize tools, network tools such as more, if we only recommend the use of surveillance, then compact monomon can, of course, if the custom-house to set up traffic monitoring site or service center If you can use other support SNMP-MRTG, PRTG, such as instrument. We can http://monomom.matf.de/download.php address to download the program, the whole process only one document)

循环码下RS码的编码译码，频谱图的生成，可看到信道编码效果。(Under the cyclic code coding decoding of RS code spectrum generated, can see the effect of channel coding.)

计算认知无线系统中跳频信道接入方案有效容量的函数。(Computational Cognitive radio system hopping channel access scheme effective capacity of the function.)

基于MATLAB的模式识别的贝叶斯决策，处理水环境分类问题，共分为5类，最后得出五类总的识别率。 (Bayesian decision pattern recognition based on MATLAB, the problem of classification of water environment treatment, is divided into 5 categories, finally obtains five kinds of total recognition rate. )

RBTS可靠性测试系统数据在matlab编程中可直接调用的小程序(RBTS reliability test system data in Matlab programming a small program that can be called directly)

nelder-mead算法,程序不算太长，应该好理解，仔细看几遍就行了(nelder-mead method， it is very useful if you want it,just download it!)

支持向量机和BP神经网络虽然都可以用来做非线性回归，但它们所基于的理论基础不同，回归的机理也不相同。支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。为了验证这种观点，本文编写了支持向量机非线性回归的通用Matlab程序和基于神经网络工具箱的BP神经网络仿真模块，仿真结果证实，支持向量机做非线性回归不仅泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。 (Support Vector Machine and BP neural network, even though there can be used to make non-linear regression, but they are based on the theoretical basis for the different, the mechanism of regression is not the same. Support vector machine based on structural risk minimization theory, generally considered the generalization ability of neural networks than the strong. To test this view, the paper prepared by non-linear regression support vector machine procedures and based on a common Matlab neural network toolbox of BP neural network )

基于matlab的有限元程序源代码，希望大家喜欢(Based on the finite element program matlab source code, I hope everyone likes)