S-I-F-T_YantaoNoemie

说明：  MATLAB的CDMA仿真(MATLAB simulation of CDMA)

摘要地层控制分析与设计问题 无人机（UAV）群系统实现时间。 研究了不同的地层。达到预定时间- 无人机的编队、编队协议各不相同。 首先是群系统，无人机的速度可能不同 当到达编队时。然后，基于共识的方法 用于处理时变信息的形成控制 无人机群系统的问题。必要和充分 无人机群系统实现时变的条件 提出了构造方案。(Abstract-formation control analysis and design problems for unmanned aerial vehicle (UAV) swarm systems to achieve time. varying formations are investigated. To achieve predefined time- varying formations, formation protocols are presented for UAV swarm systems first, where the velocities of UAVS can be different when achieving formations. Then, consensus-based approaches are applied to deal with the time-varyin formation control problems for UAV swarm systems. Necessary and sufficient conditions for UAV swarm systems to achieve time-varying formations are proposed.)

对序列建立AR模型，并以概率形式给出预测数列表达。先进行平稳性检验后求取自相关函数，用Y-W法求取模型参数，并应用FPE准则确定阶数，进行预测后，给出概率表达。(AR model for the sequence established, and the probability forecast given in the form of a list. After a smooth first autocorrelation function test strike strike model parameters YW law and apply the criteria to determine the order of FPE, predict, given the probability of expression.)

matlab图像处理作业，对一段视频中的运动物体进行实时跟踪。利用surf进行每两帧图像的配准，并利用帧间差分法，找到物体轮廓，可追踪两个目标，请在matlab2013b环境下运行(Matlab image processing operations, real-time tracking of a moving object in video. Using surf every two frames of image registration, and use the interframe difference method, find the object contour, traceable two objectives, please run in matlab2013b environment)

基于四个移位寄存器的最小二乘递推算法辨识程序(Shift register based on the four identification procedures recursive least squares algorithm)

说明：  MATLAB预测程序(MATLAB forecasting process)

压缩感知简介,包括压缩感知具体实现过程，最基本的原理说明(compressive sampling)

该程序可以用作计算谐振器的传输特性，包括透过率、相移、色散、延迟等。(describe resonator)

两发两收的空间多路复用信道的matlab仿真程序。(Two received two space multiplexing channel matlab simulation program.)

说明：  M/M/m排队系统性能仿真代码matlab function r=randexp(lambda) r = -lambda*log(rand) (M/M/m queuing system performance simulation code matlab function r = randexp (lambda) r =-lambda* log (rand))