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说明：  此MATLAB程序用于读取MIT-ECG数据、将二进制数据转换为十进制数据(The MATLAB program used to read the MIT-ECG data, binary data is converted to decimal data)

遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的(Genetic Algorithm (based Algorithm) is a simulation Darwin the evolution natural selection and Genetic mechanism of biological evolution process calculation model, is a kind of searching optimal solution by simulating the natural evolution process of the method, it initially by the university of Michigan J.H olland first proposed in 1975, professor)

a fifth version of Dsp view code in matlab

对表面肌电信号的分析处理的Matlab程序，包括：求频谱、倒谱、功率谱和中值频率等。(Surface EMG signal analysis and processing in Matlab, including: the demand spectrum, cepstrum, power spectrum and the median frequency.)

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an introduction to dynamic meterology chapter one matlab所有代码 气象专业经典资料(an introduction to dynamic meterology chapter one matlab code)

Kalman 滤波和平滑工具箱，包括了1. Kalman 滤波和平滑 2. EKF 和 平滑 3. CKF 和平滑 4. UKF 和平滑 5. GHQF 和平滑 6. IMM 滤波和平滑 (EKF/UKF is an optimal filtering toolbox for Matlab. Including: 1. Kalman filters and smoothers 2. Extended Kalman filters and smoothers 3. Unscented Kalman filters and smoothers 4. Gauss-Hermite Kalman filters and smoothers 5. Cubature Kalman filters and smoothers 6. Interacting Multiple Model (IMM) filters and smoothers)

自适应线性预测编码问题，计算LMS迭代时预测误差和系数误差的功率谱，绘出残余能量曲线和学习曲线(Adaptive linear predictive coding problem, when calculating the LMS iterative prediction error and coefficient error power spectrum, plotted the residual energy curve and learning curve)

入色偏角为0.5°太阳光聚焦程序设计，方便大家学习于应用。(Into color declination 0.5 ° sunlight focused program designed to facilitate learning in the application.)

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)