fulore1_fu

书名为《Matlab神经网络工具箱应用简介》。通过阅读这篇文档即能对Matlab中的神经网络工具箱的使用有所了解。(book entitled "Neural Networks Toolbox Matlab Application Profile." By reading this document that is able to Matlab neural network toolbox is the use of understanding.)

基于EM算法实现的高斯混合模型数据分类，可以很优秀的对各种数据进行聚类分析，R语言实现(EM algorithm based on Gaussian mixture model data classification, can be very good for a variety of data clustering analysis, R language)

文件是雷达设计使用的matlab源代码，其参考的是书籍《radar design with matlab》(document is designed to use radar Matlab source code, its reference books "radar design with Matlab")

太阳能模糊控制封装模块，根据太阳能电池特性曲线设计的模糊控制器，通过设置规则封装成模糊控制模块(Solar fuzzy control package module according to the solar cell characteristic curves designed fuzzy controller by setting the rules package into the fuzzy control module)

This contains just the pure aloha

VIDEO ENCODING IN MATLAB

The goal of segmentation is to simplify and change the representation of an image into something that is more meaningful and easier to analyze. Here similar looking pixels are grouped together for efficiency of further processing. In segmentation a label is assigned to every pixel in an image such that pixels with same label share certain visual characteristics. There are many methods and algorithms to segment an image. Mean shift Algorithm is also an algorithm which can be used to segment a color image.

利用遗传算法来进行一个cybershake科学工作流的开发！(a GA based algorithm for cybershake workflow scheduling!!)

说明：  协调控制算法，基于发电厂锅炉与汽轮机模型，首先将模型离散化，然后实施控制算法(Coordinated control algorithm, based on power plant boiler and steam turbine model, discrete model first and then the implementation of control algorithms)

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)