DCtoACPWMconverter

ieee各种节点图形，仅供参考。电力系统的分析和计算中，需要不同网络结构和参数。在应 用这些参数之前，收集和整理工作会花费大量的时间和精力。(ieee various node graph, for reference only. Power system analysis and calculation, require different network structures and parameters. Before applying these parameters, the collection and collation will spend a lot of time and effort.)

调试成功的测距定位仿真（TOA）。三个函数的作用分别是：在一个正方形区域内随机选择10个点；在这10个点中选择被测结点和参考结点；LSE位置计算。(Ranging and Location debug successful simulation (TOA). The role of the three functions are: a square area in 10 randomly selected points 10 points in the selected node under test and reference nodes LSE position calculation.)

线性调频信号脉冲压缩雷达仿真程序 脉冲压缩实现(Chirp signal pulse compression radar simulation )

说明：  内点法求解IEEE-30bus电力系统经济调度问题(Interior Point Method for Economic Dispatching of IEEE-30bus Power System)

本源码为利用光流法提取视频关键帧的matlab程序实现，也是本文基于内容的视频检索的论文所写的代码，需要的可以参考！(The source for the use of optical flow extracted keyframe Videos matlab program implementation, but also this article content-based video retrieval dissertation written code, can refer to the required!)

说明：  用matlab实现的热核在路由及网络拓扑上的分析(Using matlab to achieve thermonuclear in routing and network topology analysis)

program to code some properities in chaos

ofdm mimo MATLAB仿真(ofdm mimo MATLAB simulation)

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 .)

两篇关于语音信号处理的文章，对于语音初学者来说相当实用，希望对大家能有所帮助(Two articles about the speech signal processing for voice beginners very useful, I hope that we can help)