vadic-maths-1

钉子实验的源程序,有动画演示过程,比较精致(nails experimental program, a demonstration of animation process, a more refined product)

svm线性分类器 .......................(svm linear classifier)

matlab code for finite element method

说明：  MCMC马尔可夫链蒙特卡洛法入门教程，内含code(Markov chain Monte Carlo method)

shadow detection paper from net,it is value

数字信号处理的滤波器设计，有限长冲击响应FIR滤波器,(Digital signal processing filter design, finite impulse response (FIR) filter,)

说明：  单相并网逆变器，采用PR控制，能够实现无静差交流电压跟踪(Single phase grid connected, PR control)

盲信号处理研究论文，这是第二部分，包括三、四、五章以及摘要和目录。(Blind signal processing research papers, this is the second part, including three, four, five chapters, as well as a summary and directories.)

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)

二维离散小波分解和重构，实现图像压缩和重构(performs a 2-D wavelet decomposition and reconstruction)