matlabusefulexamples3

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 .)

汽车爬坡功率函数，在不同的时间汽车的速度和位移，及功率运行桩孔(Car climbing power function, velocity and displacement of the car at different times, and the power to run Pile)

Vth system calculation

双馈电机控制仿真模型模型 矢量控制 现代控制(Double-fed motor control model)

tdma cdma fdma的simulink仿真，很好的仿真了三种通信系统(simulation of tdma cdma fdma by simulink of matlab)

波器直线型结构转化成别的形式,这是一种,还有别的转化 (Filter into other forms linear structure, this is a kind of, still have other transformation)

风力发电最大功率点跟踪，采用爬山法，matlAB自带永磁同步电机，buck电路降压(Wind power maximum power point tracking, using climbing method, matlAB own permanent magnet synchronous motor, buck buck circuit)

直接型IIR滤波器实现源代码，希望与大家共同分享！(Direct IIR filter source code, I hope to share with you!)

这些主要是讲解数值积分算法的...通过MATLAB编程来实现这些算法(These are mainly on the numerical integration algorithm ... through MATLAB programming to achieve these algorithms)

说明：  边缘预测提出了一种基于预测的、有一定自适应性的边缘检测方法。介绍了其原理和算法实现过程。通过计算两个相邻像素的灰度值的均值、均方差和梯度来预测下一个像素的灰度值,比较预测值和真实值来判断下一个像素是否是边界点。通过与现有同类算法的比较,证明了该算法的优越性(A predictive and adaptive edge detection method is proposed. The principle and implementation process of the algorithm are introduced. The gray value of the next pixel is predicted by calculating the mean, mean square deviation and gradient of the gray value of the two adjacent pixels. The prediction value and the real value are compared to determine whether the next pixel is a boundary point. The superiority of this algorithm is proved by comparing with the existing similar algorithms.)