DS_fusion

designing pi and pid controllers using feedback.

對影像做物件標籤，並且分別提出不連續的影像作編號。(Do object to the image tag, and the images were made discrete for number.)

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)

This is the matlab soution manual for the execrsis behind the chapeter 7 of AFT text book

lms算法对信号进行线性预测，程序非常棒，欢迎借鉴(lms algorithm for linear prediction signal, the program is great, welcome to learn)

基于HHT提取昆明下关重力固体潮的地震前兆信息(Based on the HHT earthquake precursor information extraction of kunming where the tidal gravity )

本文利用matlab数值求解CO2在碳酸饮料中的流失问题，并根据模拟结果对影响因素进行了理论分析，给出了碳酸饮料保证口感的关键因素(In this paper, numerical solution matlab CO2 in carbonated drinks in the loss of, and factors influencing the results of simulation carried out theoretical analysis, the taste of carbonated beverages a key factor in ensuring)

Crossover fron generic algorithm, matlab

Introduction: The goal of the HumanEva dataset is to develop new techniques, technology, and algorithms for the automatic articulated pose estimation and tracking of humans. Brown University is involved in an ongoing effort to develop this dataset of synchronized video and motion capture data. The dataset is meant to aid research uating algorithms for human motion estimation. Brown University has

说明：  故障诊断程序 支持向量机智能诊断 分为多个程序 数据输入、特征提取、功能函数等(Fault diagnosis procedure Intelligent diagnosis of support vector machine It is divided into several program data input, feature extraction, function function, etc)