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BP-network
matlab 基于PID控制器的BP神经网络系统的仿真(matlab PID controller based on BP neural network system simulation)
- 2011-01-07 17:24:20下载
- 积分：1
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functionEnergyEfficiency
this code is related to Energy efficiency in massive mimo system
- 2014-10-13 12:59:34下载
- 积分：1
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WE
说明： 稀疏条件下欠定盲分离，得到混合矩阵，恢复原信号(Underdetermined blind separation under sparse conditions)
- 2014-01-13 17:10:40下载
- 积分：1
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BPSK
BPSK系统结构的Matlab程序，包括升余弦波形成形，系统误码率，时延，以及说明性文档。(BPSK system architecture of the Matlab procedures, including angioplasty or cosine wave, the system bit error rate, delay, and the descriptive document.)
- 2009-04-22 09:08:30下载
- 积分：1
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xiaoboji
采用低通性质的平滑函数为高斯函数，根据他的一阶导数、二阶导数作为小波基函数进行突变点分析。
(The use of low-pass nature of the smoothing function for the Gaussian function, according to his first derivative, second derivative wavelet basis function as a point mutation analysis.)
- 2020-09-02 17:08:07下载
- 积分：1
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PMSM_flux-weakening
永磁同步电机弱磁调速系统的仿真.在矢量控制的基础上进行改进，采用弱磁调速，可作为参考.(Permanent magnet synchronous motor speed control system simulation weakening in vector control on the basis of improved, using weak magnetic speed, can be used as reference.)
- 2013-08-12 13:36:03下载
- 积分：1
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LMS_method
LMS算法，可以画出自适应滤波器系数收敛曲线(LMS algorithm, the adaptive filter coefficients can draw convergence curve)
- 2013-10-18 13:38:16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
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Single_Phase_FW(2)
Single_Phase_FW 2010
- 2011-12-12 08:25:39下载
- 积分：1
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MatlabCprogramtoghter
说明： 精通Matlab与C++混合程序设计第2版(Matlab and C++ program toghter)
- 2009-08-23 03:30:04下载
- 积分：1
