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基于小波数字图像处理MATLAB源代码 例如压缩提取 噪声水印提取等(Wavelet-based digital image processing such as compression MATLAB source code extracted watermark extraction, such as noise)

用matlab实现数字水印，课程的一个实验报告，很详细。(Digital watermarking using matlab)

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)

Principle component Analysis based face recognition system

文件包含多个源程序，包括基本MUSIC算法及MUSIC算法的多种改进算法，对各种算法进行了性能比较(File contains more than one source, including the basic MUSIC method MUSIC algorithm and a variety of improved algorithms for performance comparison of various algorithms)

seismic response analysis of MDOF structures using wilson-theta method

这是应用ｍａｔｌａｂ模拟电容充放电的过程，编写一段程序，希望对大家有用。(This is the application matlab analog capacitor charging and discharging process, the preparation of a program, in the hope that useful. )

说明：  灰色预测模型的matlab算法实现，可以进行较为长期的预测(use matlab to solve gm problem)

matlab 计算带驱动力偏微分方程poincare map，方程为dy(1)=y(2) dy(2)=-k*y(2)-y(1)^3+B*cos(t) (Matlab calculation of belt driving force of partial differential equation and Poincare map equation, Dy (1) =y (2) Dy (2) =-k*y (2)-y (1) ^3+B*cos (t) )

Pocket CRF is a toolbox for Conditional Random Fields