adaptiveequalisersandsmartantennasystems

记录我针对数字通信（John.G Proakis）版本学习中编写的仿真程序。 和大家交流共同学习，其中的错误，希望大家指证！ (I look at digital communications records (John.G Proakis) version of the study prepared by simulation program. And to facilitate the exchange of learning, in which the error, hope that means the card!)

这是一个用NATLAB编写的用于WSN中计算UKF的源程序(this resource is used to calculate the location of the UKF )

algoritm kruskala , be useful to equation and operations on connectivity a net

These are used for speech test signals

BLDC的仿真，描述了3相直流电机的仿真，并且在突加电压等情况下分别描述了电机的状态(The simulation of BLDC, describes the simulation of 3 phase DC motor, and in the case of sudden voltage respectively described click state)

获得图像局部增强时，每个象素的指数增强系数，指数增强系数有原图像中的灰度值与其周边象素比较获得([Coeff_en_local, lum_mask]=enhance_coeff_local_bilateral(lum_ori,window_r,sigmad,sigmar))

这是一个关于盲源分离独立成分分析方法（ICA）的软件包,可用图形界面操作(Here is a blind source separation independent component analysis (ICA) of the package, there are graphic interface operation)

matlab学习中常用到的一些程序代码，有助于大家学些matlab知识 (matlab)

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 .)

四阶龙格库塔数值方法，用于求解光纤光栅非线性耦合模方程，可求解正向，反向传输波幅度(Fourth-order Runge-Kutta solution of the coupled mode equation)