Basic-of-Matlab

分析并实现了跳频信号的检测方法，用程序给出仿真结果(Analysis and implementation of frequency hopping signal detection method, using the program simulation results)

电力电子逆变器MATLAB仿真模块模型，适用于微网系统MATLAB_simulink仿真环境下的研究应用。(Power electronic inverter module of MATLAB simulation model, research on the application of suitable for micro grid system MATLAB_simulink simulation environment.)

MIMO-OFDM仿真程序，包含完整的信道仿真程序，信道估计程序(MIMO-OFDM simulation program, including a complete simulation program channel, channel estimation procedures)

说明：  Rilling的关于Rilling的关于HHT端点延拓的代码HHT端点延拓的代码(Rilling Rilling on HHT endpoint extension on the code the code HHT endpoint extension)

一个EKF进行优化的例程，非常好，值得学习！(A good example of EKF, it is well worthing!)

稀疏性学习的工具包，包含说明文件和工具m文件(Sparse learning toolkit, including documentation and tools m file)

very useful source code for telecommunication

平坦Rayleig衰落的MATLAB仿真 附加资料(RAYLEIGH)

自举是一种由重采样估计，独立和（蒙特卡洛重采样）等概率设置一个单一的数据统计变化的一个途径。允许的措施估计那里的潜在分布是未知的或者样本量很小。他们的结果与这些分析方法的统计特性相一致。 在这里，我们使用非参数逼近。非参数引导更简单。它不使用该模型的结构，建造人工数据。矢量[易西]是重采样，而不是直接与replecement。这些参数是从这些对构建。 二，回归模型时，应使用在回归方程中的两个变量是随机的，会有错误的，即不是由研究者控制。模式，我用普通最小二乘回归低估了变量之间的错误时，他们都含有线性关系的斜率。据索卡尔和罗尔夫（1995），模型二回归的主题是一对哪些研究和争论仍在继续，最终建议是很难做出。 BOOTGMREGRESS模型II是一个引导程序。这需要s引导和规范样品前坡计算变量。这两个变量的每个转化为具有零均值和标准差的一个。由此产生的斜率是线性回归系数的Y在X里克创造了这个词（1973）几何平均数并给出了一个模型II回归广泛审查。它也被称为引导标准的主要轴线(The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their results are consistent with the statistical properties of those analytical methods. Here, we use the Non-parametric Bootstrap. Non-parametric bootstrap is simpler. It does not use the structure of the model to construct artificial data. The vector [yi, xi] is instead directly resampled with replecement. The parameters are constructed from these pairs. Model II regression should be used when the two variables in the regression equation are random and subject to error, i.e. not controlled by the researcher. Model I regression using ordinary least squares underestimates the slope of the linear relationship between the variables when they both contain error. According to Sokal and Rohlf (1995), t)

arc 电弧模型库，MATLAB2013版本可以运行(The arc arc model library, MATLAB2013 version can be run)