matlab

Solution of system (LU)*v=d

Simulink Model for DC motor Control

通信系统中常用的多进制数字相位调制的源代码 并结合ofdm系统 加入了相应的保护前缀（cp）和导频序列 应用于有关ofdm的信道估计等系统(Communication systems commonly used in multi-band digital phase modulation of the source code and combine OFDM system by adding a prefix corresponding protection (cp) and the pilot sequence used in the relevant channel estimation of OFDM systems)

本文主要介绍频域均衡在LTE项目上SC_FDMA上行链路上的应用(In this paper, frequency domain equalization projects in the LTE uplink SC_FDMA Application are introduced)

说明：  最小二乘一次完成算法，压缩包里以给出数据，可以运行试试看。(A complete least-squares algorithm, data compression is given a bag, you can try to run.)

说明：  用于预测航运港口利用率的神经网络模型，基于时间递推。泛化(time chain for port)

This is the m file for reading uff file using matlab. I can be easily read uff file in which to analyze the data.

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) )

时间序列分析中AR模型的建立，可求的残差平方和，便于用AIC准则定阶。(Time series analysis of AR model, rectifiable the residual sum of squares, easy to use the AIC criterion to determine the order.)

A database of facial expression images was collected. Ten expressors posed 3 or 4 examples of each of the six basic facial expressions (happiness, sadness, surprise, anger, disgust, fear) [4] and a neutral face for a total of 219 images of facial expressions.