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SVM 3分类程序 适用于信号处理、数据分类情况(SVM 3 classification procedure is applicable to signal processing, data classification)

编写的有关规划问题的函数，初学者可以参考！！！！(Planning)

说明：  对一列数据波形进行画图，频谱、功率谱分析。参数根据需要改动一下即可(Waveform data of a drawing, spectrum, power spectrum analysis. Click to change parameters as needed)

lyapunov指数总结,讲的很详细，是学习的好资料，大家快下载吧(Lyapunov index, speak very detailed, is learning good information, everyone to download)

说明：  利用NSGAII算法进行对复杂网络的社区检测(community detection in complex network)

Matlab M-Files:There are four ways of doing code in Matlab. One can directly enter code in a terminal window. This amounts to using Matlabas a kind of calculator, and it is good for simple, low-level work. The second method is to create a script M-fi le. Here, one makes a fi le with the same code one would enter in a terminal window. When the fi le is “run”, the script is carried out. The third method is the function M-fi le. This method actually creates a function, with inputs and outputs. The fourth method will not be discussed here. It is a way to incorporate C code or FORTRAN code into Matlab this method uses .mex fi les. We will not disucss it here.

灰色模型 gm(1 1) 二次拟合 matlab (gm（1，1）matab)

定位技术是无线传感器网络中关键的基础支撑技术, 目前提出了许多静态网络的节点定位算 法, 移动无线传感器网络的定位研究相对较少. 针对定位节点和参考节点随机运动的网络模型, 提出了 一个基于动态网格划分的蒙特卡罗定位算法. 算法中当接收的参考节点数超过一定阈值时使用最远距 离节点选择模型, 选出部分参考节点参与定位和信息转发, 节约能耗. 接着基于选择的或所有接收的参 考节点构建采样区域, 进行网格划分, 使用网格单元数计算最大采样次数, 在采样区域内采样并使用误 差补偿的运动模型进行过滤, 提高了采样效率, 减少了计算开销, 并保证了较好的定位精度. 仿真实验表 明算法在定位精度, 计算开销、能耗等方面都具有较好的性能.(Positioning technology is critical in wireless sensor networks based supporting technologies, currently made many static network node localization algorithms, the positioning of mobile wireless sensor network research is relatively small. Locate node and a reference node for random motion network model, proposed a Dynamic meshing based Monte Carlo localization algorithm. algorithm when the received reference nodes exceeds a certain threshold, the most distant node selection model selects some reference nodes involved locating and forwarding information, save energy. then based on the selection or building all received reference node sampling area, meshing, the number of grid cells used to calculate the maximum sampling frequency, the sampling area sampling and using motion model error compensation filter to improve sampling efficiency, reducing the computational overhead and to ensure a better positioning accuracy. Simulation experiments show that the algorithm in positioning accuracy,)

BP network is a wide used network in Artificial Neural Network domain. This is a example of BP, applied with Matlab!

Constrained Optimization of MIMO Training Sequences