libsvm

SimPowerSystem 是MATLAB的一个工具箱，主要用于电力系统、电力电子电路的仿真。(SimPowerSystem is a MATLAB toolbox, is mainly used for electric power systems, power electronic circuit simulation.)

通过matlab编制程序，对非线性方程组迭代求解。(Through matlab programming, iterative solution of the nonlinear equations)

最小费用流问题用于求解，图论中两地区运输费用最少的问题，本程序通过MATLAB解决这一问题(For solving the minimum cost flow problem in graph theory two least-cost regional transportation issues, the procedure to solve this problem through MATLAB)

说明：  结合DBPSK(Differential Binary Phase ShiR Keying)的LT码进行了深入的分析与仿真研究，重点讨论了LT码与调制的联 合优化问题。(The LT code combined DBPSK (Differential Binary Phase ShiR Keying) conducted in-depth analysis and simulation study focused on a the LT code modulation joint optimization problem.)

This is the cuckoo optimization code 2

说明：  超宽带无线电信号码元simulink仿真(Ultra-wideband wireless telecommunications numbers per simulink simulation)

应用于图像增强领域，采用多级分层的图像增强技术，源自王大凯版图像增强源代码。(Used in the field of image enhancement, multi-level hierarchical image enhancement technologies, from Wang Taikai source code version of image enhancement.)

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)

friction model simulink

对于加载的接收天线的频率宽度进行优化设计(Optimal Design of Broadband Loaded Receiving Antenna)