simplecharrec(I&II)

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)

用前推回代法编写了一个算8节点配网潮流的程序，解压后就可以直接运行(With forward and backward substitution method to write an 8-node distribution network power flow calculation program, named after the needs of the non-alphanumeric characters removed after decompression, it can be run directly)

emd算法部分程序 对于使用EMD的初学者来说很有好处 建议看看(the emd algorithmic part of the program for beginners )

LTE for UMTS OFDMA and SCFDMA Based Radio Access

说明：  MIMO系统中的经典的V-Blast代码，是一位博士写的，作为我的程序参考资料用的。运行过，正确无误。(MIMO system, the classic V-Blast code, written by a PhD, as my reference material used in the procedure. Run over, correct.)

应用支持向量机回归和相空间重构对时间序列进行预测(Support vector machine regression and time series phase space reconstruction on forecast)

sinc插值函数，在SAR、ISAR，通信等信号处理中有广泛的应用，是非常好的学习代码。(sinc interpolation function, there is a wide range of applications in the SAR, ISAR, communications and other signal processing, is a very good learning code.)

Matlab中龙格-库塔(Runge-Kutta)方法原理及实现(Matlab, Runge- Kutta (Runge-Kutta) method principle and implementation)

本代码可以实现绕过win7UAC（用户账户控制），可以很好的实现(This code can realize to bypass win7UAC, (User Account Control), can achieve a good)

Image_processing_in_Matlab(in persian)