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Programming
包括各种规划问题的文档和程序，无约束优化，线性规划等等(Including planning documents and programs, unconstrained optimization, linear programming, etc.)
- 2011-04-26 20:41:51下载
- 积分：1
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P6Gaussian
gaussina lOW PASS FILTER
- 2014-09-21 01:46:20下载
- 积分：1
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shuzixinhaochuli
我们做很多实验时得到的一些数字信号必须经过处理才能最终得到应用。此文件是matlab数字信号处理说明书，希望对读者有帮助(We do a lot of experiments to get some of the digital signal must be processed in order to ultimately be applied. This file is matlab digital signal processing instructions, hoping to help the reader)
- 2013-10-27 21:16:59下载
- 积分：1
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my_wthresh
软硬阈值函数和自定义的基于非线性变换阈值函数曲线图(Hard and soft threshold function and custom thresholding function based on nonlinear transformation curve)
- 2010-12-21 15:33:09下载
- 积分：1
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julei
荧光光谱聚类分析软件，可对物质的荧光光谱进行分类。(Fluorescence spectroscopy analysis software for clustering)
- 2009-07-20 21:20:03下载
- 积分：1
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code
说明： GA-BP神经网络，包含数据和代码，绝对好用，亲测有效(GA-BP neural network, including data and code)
- 2020-09-26 22:03:08下载
- 积分：1
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ROMP
Regularized OMP by Vershyn and Kneedell
- 2021-03-26 22:09:12下载
- 积分：1
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chaxunriqi
使用matlab查询日期的方法，有需要的看看。(The date of the use of matlab query methods, there is a need to look at.)
- 2008-06-05 22:57:12下载
- 积分：1
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编码及误差分析QUANTIZE
u率pcm编码,还有误差分析,通信原理实验的一个例子(u rate PCM coding, error analysis, communication principle of an experimental examples)
- 2005-06-05 21:17:15下载
- 积分：1
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bootgmregress
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)
- 2011-05-21 13:19:38下载
- 积分：1
