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LTE_A_PUSCH
LTE上行双用户matlab仿真代码，用户单天线，基站8天线。(LTE uplink dual-user matlab simulation code, user single antenna, base station 8 antenna.)
- 2020-12-17 19:09:12下载
- 积分：1
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shiftbits
这是一个虹膜识别检测的程序，只是虹膜识别的功能函数定义(This is a test of iris recognition procedure, only the definition of iris recognition performance function)
- 2010-07-24 10:16:56下载
- 积分：1
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Noname
在进行层次分析时，用于计算一致性矩阵，检验一致性。(In the level of analysis, used to calculate the consistency matrix, the consistency test.)
- 2009-03-23 14:36:06下载
- 积分：1
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Porjection3
变分不等式求解算法之一，投影算法是将变分不等式的解进行投影，然后进行迭代。(One of the variational inequality solution algorithm, the projection method for variational inequality solution to the projection, and then iterate)
- 2021-03-16 20:39:21下载
- 积分：1
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EKF_UKF_RMSE
EKF(扩展卡尔曼滤波)和UKF（无迹卡尔曼滤波）对比 RMSE曲线对比(Contrast curve comparison RMSE (unscented Kalman filter) EKF (extended Kalman filter) and UKF)
- 2016-04-29 10:37:44下载
- 积分：1
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PCA5555
核PCA和PCA用于故障检测与诊断，对故障有很好的监控能力(Nuclear PCA and PCA for fault detection and diagnosis of faults have a good monitoring capability)
- 2011-10-20 22:32:39下载
- 积分：1
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good-random-number-generator-
在matlab下运行，产生标准均匀分布，正态分布和指数分布的随机数发生器程序。(In matlab running, generate standard uniform, normal and exponential distribution random number generator program.)
- 2013-09-15 20:39:38下载
- 积分：1
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DCmotor
simulink file for a dc motor with PID
- 2014-01-25 09:29:01下载
- 积分：1
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stegano_src
matlab description for image stéganography
- 2011-04-20 20:20:20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
