干扰滤波器组的多载波

RBF网络用于函数逼近的一个程序！内部包含几个关于RBF网络的几个算法。(RBF network for function approximation of a process! Internal contains several of the RBF network of several algorithms.)

说明：  关于瑞利衰落的一段很实用的代码。特别在BPSK调制中对于学习通信方面的同学很有帮助。(Rayleigh fading on a very useful code. BPSK modulation, especially in communications for students to learn helpful.)

此程序为基于LMS的自适应均衡器的仿真，取得信号为4QAM信号(This program for the simulation of the LMS-based adaptive equalizer to obtain the signal for 4QAM signal)

一个对RBF进行改进的程序，其中有演示的例子-1 pairs of RBF to improve procedures, including examples of presentation

说明：  潮流计算，电力系统潮流计算。从已知节点数据计算牛顿潮流(Power flow, power system flow calculation. Newton calculated from the known trend of the data node)

蜘蛛网迭代法做Logistic模型的轨道(Logistic model of iterative methods to make spider web track)

摘 要: 利用MATLAB平台的SIMULINK功能编写了一套QDPSK通用功能模块库，并在此基础上进行了多项可视化仿真,较 好地显示了数字通信的工作方式和优越性，以及采用SIMULINK进行仿真的良好的演示效果，为QDPSK数字通信系统的研究提 供了一个较好的软件平台。(Abstract: This paper gives a group of module library for digital communication function applying MATLAB’ s SIMULINK function， and offer a group of software to perform the visualizing simulation. The software perfectly shows the advantage and the process of normal digital communication. More over, it provides a software base for further study on QDPSK Digital communication.)

This report considers trajectory planning with constrained dynamics and design of an appropriate feedforward controller for single axis motion control. A motivation is given for using model-based fourth order feedforward with fourth order trajectories. An algorithm is given for calculating higher order trajectories with bounds on all considered derivatives for point to point moves. It is shown that these trajectories are time-optimal in the most relevant cases. All required equations for third and fourth order trajectory planning are explicitly derived. Implementation, discretization and quantization effects are considered. Simulation results show the superior effectiveness of fourth order feedforward in comparison with rigid-body feedforward

1.CAmodelfusion.m 主要功能： （1）完成两个传感器各自对基于CA模型的目标状态的Kalman估计； （2）实现传感器的局部状态估计的SCC和CI融合算法的实现； （3）画出局部估计和两种融合估计的位置、速度、加速度的误差； （4）画出局部估计和两种融合估计的协方差椭圆。 2.CVmodelfusion.m 主要功能： 功能与CAmodelfusion.m基本相似，差异在于实现基于CV模型的估计和估计融合。 3.CovInter.m 主要功能： 寻找CI融合算法的融合估计的协方差阵的行列式最小的权值。 4.f_plot_ellipse_m.m 主要功能： 绘制四种估计的协方差椭圆 (1.CAmodelfusion.m main functions: (1) completion of two sensors each target state based on CA model of Kalman estimation (2) the realization of the sensor partial state estimation algorithm SCC and CI integration and (3) Draw Local estimated position and two fusion estimation, velocity and acceleration errors (4) Draw two fusion of local estimates and estimated covariance ellipse. 2.CVmodelfusion.m Main Features: a CAmodelfusion.m similar, the difference is that the estimated CV-based estimation and model integration. 3.CovInter.m main functions: Find fusion algorithm fusion CI estimated covariance matrix of the determinant minimum weight. 4.f_plot_ellipse_m.m main functions: Draw four kinds estimate covariance ellipse)

格兰杰因果关系检验同时应用于 matlab。这是统计假设检验 确定一个时间序列是否有用在预测另一种。这 是确定是否一个时间序列的统计假设检验 在预测另一种是有用的。在这个 Matlab 函数输入 X、 Y、 最大值 滞后和名称的变量。 时间序列 X 是对格兰杰原因 Y 说，如果它可以是 所示，通常通过一系列的 t 检验和 F-检验对 X 的滞后值 （和滞后的还包括 Y 的值），这些 X 值提供 未来值的 Y.统计学信息结果将 印在 Matlab 命令窗口。它也自动测试示例 本身如果你不知道如何使用它。