rectangular-filter

一些常用的matlab程序，对于入门学者有很大的帮助，每一个程序均有详细的说明(Some commonly used matlab program for entry scholar of great help, every program has a detailed description)

该段程序是实现支持向量机的重要支撑，对于初学者来说有很大的帮助(This procedure is to realize the important support of support vector machine (SVM), is of great help for beginners )

说明：  雷达目标航迹跟踪，运行函数main_test，进行雷达数据处理，最终显示航迹；(Radar Target Tracking，Run the function main_test, the radar data processing, the final display track )

INS捷联惯导解算 使用四阶龙格库塔法 并附仿真数据一份(INS strapdown solver attached to the simulation data of a)

故障诊断相关的MATLAB代码，主要有神经网络算法的m文件(MATLAB Code Related to Fault Diagnosis)

主要是MATLAB与VC的链接，是从别人哪里弄过来的，和大家一起分享一下！希望对大家可以有用!~~(MATLAB and VC are the main link where other people get from the back, and to share with everyone! Hope everyone can be useful! ~ ~)

performance description for codes in LTE applications

一本的电磁数值分析方面的，集有限差分法，有限元法和矩量法为一体的基础教材。(An electromagnetic numerical analysis, set finite difference method, finite element method and the method of moments as one basis for teaching materials.)

说明：  样本自相关函数和偏相关函数，仅供大家参考，多多指教(Sample autocorrelation function and the partial correlation function, we only refer to the exhibitions)

城市交通流的运行存在着高度的复杂性、时变性和随机性,实时准确的交通流预测是智能交通系统,特别是先进的交通管理系统与先进的出行者信息系统研究的关键. 基于交通流预测的特点,给出了基于遗传算法的小波神经 网络的交通预测模型GA-WNN ,用具有自然进化规律的遗传算法来对小波神经网络的连接权值和伸缩平移尺度进行前期优化训练,部分代替了小波框架神经网络中按单一梯度方向进行参数优化的梯度下降法,克服了单一梯度下降法易陷入局部极小和引起振荡效应等缺陷. 仿真实验验证了GA-WNN 预测模型对短时交通流的预测的有效性.(For the high complexity ,time-variation and probability of urban traffic flow , its real-time and exact prediction is critical to the research of intelligent traffic systems , especially for the advanced traffic manage-ment system and advanced traveler information system. Based on the character of the traffic flow prediction , a GA-WNN model is given based on the wavelet neural network with genetic algorithm. The genetic algorithm of natural evolving law for the gradient descendent algorithm in Wavelet Neural Network is partly substituted to pre-optimize the connection weight and the extension scale of the wavelet neural network and later optimize the parameters along a single gradient vector. This method overcomes some drawbacks when there exists a single gradient descendent algorithm , such as local minimum and oscillation. A short-time traffic flow prediction sim- ulation using the GA2WNN prediction model demonstrates the validity of the model .)