GW_transport_TEST.m.tar

growcut image segmentation gui

QPSK仿真，实现，matlab，m文件(QPSK simulation)

voice processing MATLAB toolbox

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 .)

Detecting the presence of smoke in videos can be a very critical as it is a prior sign of fire. Once this technique is implemented with improved accuracy, it has the potential to avoid damages to both lives and property.

说明：  matlab实现一些基础的模式识别工作，如贝叶斯分类，聚类算法，bp神经网络(Matlab implements some basic pattern recognition work, such as Bayesian classification, clustering algorithm, BP neural network)

This is 1D, 2D, 3D earth quake ray tomography forward and inverse procedures

关于极限学习机在脑电信号中的应用的主程序表示说明(About extreme learning machine in the application of brain electrical signal of the main program said )

目标跟踪卡尔曼滤波很好用,自己编的程序可以借鉴一下(Target tracking Kalman filter good use, own programs can learn about)

current perturbation identification