kalman

基于IEEE802.11a标准的星座图解调源程序， 包括BPSK,QPSK,16QAM,64QAM(Based on IEEE802.11a standard tune source constellation diagrams, including BPSK, QPSK, 16QAM, 64QAM)

一个关于MMSE算法的仿真实现，是时域均衡MMSE仿真的实用教程(A simulation of MMSE algorithm implementation, it is time domain equalization MMSE simulation practical tutorial)

说明：  该程序试图对具有31个城市的VRP进行求解，已知的最优解为784.1，我用该程序只能优化到810左右，应该是陷入局部最优，但我不知问题出在什么地方。请用过蚁群算法的高手指教。 蚁群算法的matlab源码，同时请指出为何不能优化到已知的最好解(The program attempts to have 31 cities of the VRP is solved, the optimal solution is known as 784.1, I use the program can only be optimized to about 810, should fall into local optimum, but I do not know where the problem is. Please teach master ant colony algorithm used. Ant colony matlab source, also please explain why not optimize the best solution to a known)

TDOA matlab实现对信号的时延估计，代码量少，经过验证(TDOA matlab implementation of the signal delay estimation, less code, proven)

关于复杂网络中基于耦合映像格子的WS网络相继故障程序,正常运行。对比全局耦合映像格子及无尺度耦合映像格子。(ws_cml,compared to global_cml and ba_cml, can be run right.)

天气雷达数据处理，该函数可以读取nc格式的雷达数据(Weather radar data processing, this function can be read nc radar data format)

matlab基于HMM的语音识别完整代码(需要修改程序里的路径以找到文件)(matlab)

维纳滤波，可以有效地滤除信号中的噪声,适应于某些工程(Wiener filtering.It can effectively filter the noise in the signal.Suitable for some projects)

简介：IFP_FCM,改进型FCM(模糊C均值)聚类算法,由Frank Hoppner与Frank Klawonn于2003年提出,解决了FCM算法对初始值设定较为敏感、训练速度慢、在迭代时容易陷入局部极小的问题。并附带了Box和Jenkins煤气炉数据模型辨识实例。 文件清单： IFP_FCM算法原始论文： Improved fuzzy partitions for fuzzy regression models.pdf 程序清单： IFP_FCM.m - IFP_FCM算法主函数 initifp_fcm.m - initifp_fcm子函数 stepifp_fcm.m - stepifp_fcm子函数 distifp_fcm.m - distifp_fcm子函数 IFP_FCM_T_S_box_test.m - IFP_FCM测试实例：Box和Jenkins煤气炉数据T-S模糊模型辨识 数据文件： box_data.mat - Box和Jenkins煤气炉数据(IFP_FCM, modified FCM (Fuzzy C-Means) clustering algorithm, in 2003, proposed by Frank Hoppner and Frank Klawonn, FCM algorithm to solve the initial value setting is more sensitive, slow training, while iterating easy to fall into local minimum problem. And comes with Box and Jenkins gas furnace model identification data instance.)

libsvm工具箱，用于分类的绝佳工具，也可用于非线性回归及预测，或拟合，其中文本分类是其长项，回归性能非常好(libsvm toolbox, an excellent tool for the classification can also be used for non-linear regression and forecasting, or fitting, of which text categorization is its long entry and return to a very good performance,)