QPSK-simulation

Average mutual information

遗传神经网络matlab代码好好好好好好好(Genetic neural network matlab code good good good good good good good)

function [CellSpace_nextstep VehicleSpace] = CountingNextStepVehicleState(CellSpace_current,CellSpace_nextstep,VehicleSpace,TakenMat, TakenCarIDMat,VMAX,signalFlag,UseLaneChangingModelFlag) 计算下一时刻的元胞空间状态 获取当前时刻元胞空间中的车辆信息， [VehicleInCellSpaceMat]=GetVehicleInCellSpace(CellSpace_current,TakenMat,TakenCarIDMat) if isempty(VehicleInCellSpaceMat) == 1 如果为空 return end 对每个车辆进行遍历， 获取每个车辆的数据，以及邻居车辆的数据 计算每个车辆的下一时刻状态并更新到下一时刻的元胞空间中 [CellSpace_nextstep VehicleSpace] = UpdataCellSpaceWithVehicleInfo(CellSpace_current,CellSpace_nextstep,VehicleSpace,VehicleInCellSpaceMat,VMAX,signalFlag,UseLaneChangingModel(function [CellSpace_nextstep VehicleSpace] = CountingNextStepVehicleState(CellSpace_current,CellSpace_nextstep,VehicleSpace,TakenMat, TakenCarIDMat,VMAX,signalFlag,UseLaneChangingModelFlag) 计算下一时刻的元胞空间状态 获取当前时刻元胞空间中的车辆信息， [VehicleInCellSpaceMat]=GetVehicleInCellSpace(CellSpace_current,TakenMat,TakenCarIDMat) if isempty(VehicleInCellSpaceMat) == 1 如果为空 return end 对每个车辆进行遍历， 获取每个车辆的数据，以及邻居车辆的数据 计算每个车辆的下一时刻状态并更新到下一时刻的元胞空间中 [CellSpace_nextstep VehicleSpace] = UpdataCellSpaceWithVehicleInfo(CellSpace_current,CellSpace_nextstep,VehicleSpace,VehicleInCellSpaceMat,VMAX,signalFlag,UseLaneChangingModelFlag) )

自己学习svm，编写的几个svm实例代码(Their own learning svm, svm example code written in several)

正确的潮流计算程序,经多个算例验证了正确性,值得一看(Calculation of trend right by a number of examples to verify the correctness, see)

awgn channel simulation

matlab函数速查手册,可以迅速查找常用的函数(matlab help for quickly search for functions)

本论文的工作是对近场圆形阵列宽带信号进行处理，获得目标/焦点位置增益输出， 预先定义宽带信号阻带的旁瓣衰减大小以及感兴趣频域内的恒定波束宽带模式。本文使 用不同的方法解决这个设计问题，该问题分为两部分，第一部分解决频域内的模型设计， 第二部分给出时域内的结果。仿真结果表明解决方法的有效性。 (This thesis work is a circular array of broadband near-field signal is processed to obtain the target/focus position gain output, Pre-defined stopband sidelobe wideband signal attenuation constant beam size and frequency domain of interest wideband mode. This paper makes To solve this problem in different ways design, the problem is divided into two parts, the first part of the solution in the frequency domain model design, The second part gives the result in the time domain. The simulation results show the effectiveness of the solution.)

Routine to calc who succeeded in a class based on grade

基于遗传算法的VRP程序，主要是其中几个操作，用c++编写(VRP procedures based on genetic algorithms, several of which operate mainly with the preparation of c++)