-
g_fitting
使用正交多项式完成数据拟合。程序对读入的gps采样点完成曲线拟合。()
- 2007-08-01 18:25:08下载
- 积分：1
-
LSTM_learn-master
采用LSTM算法用python语言实现的信号时间序列预测，可预测信号的占用度(The LSTM algorithm is used to predict the signal time series in python language)
- 2017-10-13 09:45:28下载
- 积分：1
-
fit_func
Fitting curve distribution function拟合曲线分布函数(Fitting curve distribution function)
- 2016-04-13 17:06:43下载
- 积分：1
-
Chase
用追赶法求解三对角方程组。在输入文件中读入矩阵和列向量，程序会在结果文件中返回结果。(Solving Three Diagonal Equations by Catching)
- 2017-03-06 21:50:32下载
- 积分：1
-
Simpleequationstoachieve
说明： 利用该方程组求解一般的线性方程组，别且符合数学求解原理(Using the equations of linear equations in general, do not and in accordance with principles of mathematics to solve)
- 2010-04-22 10:38:10下载
- 积分：1
-
PMFFTaddF
PMF FFT捕获技术捕获性能仿真，并与改进的捕获技术捕获性能比较(FFT PMF capture technology capture performance simulation, and capture performance comparison with the improved capture technology)
- 2015-06-17 14:27:53下载
- 积分：1
-
11
说明： 用二分法求解一元五次非线性方程的实数解，在高等电路学习中有很好的用途。(One yuan of five nonlinear equations dichotomy solving real solutions, there is a very good use in the higher circuit learning.)
- 2012-10-27 20:52:45下载
- 积分：1
-
aitejin
艾特金迭代法求解线性方程组源代码，在程序中修改方程就可以(Aitkin iterative method for solving linear equations source code, the equation can be modified in the program)
- 2012-06-03 16:08:11下载
- 积分：1
-
SM3
python编写SM3密码杂凑算法,测试字符串abc, abcd*16(written in python SM3 password hash algorithm, the test string abc, abcd.* 16)
- 2012-08-04 15:34:55下载
- 积分：1
-
Matlabcodes-RobustPCA
Matlab codes for Robust PCA multivariate control chart(Robust PCA multivariate control chart mainly consists two steps:
Step1
Calculates the robust mean and the robust
covariance of original dataset using the
minimum covariance determinant (MCD).
In MCD technique, finding a subset
containing half of the data such that its
covariance matrix has the lowest determinant, then using this subset to
calculate the robust mean and the robust
covariance matrix (Hubert, Rousseeuw, &
Branden, 2005)
Step2
Standardize data using robust mean and
robust standard deviation from Step1.
Apply PCA analysis, calculate the principalcomponent score matrix Y=ZA, where Z is the robust standardized data matrix, and
A is p*p matrix of eigenvectors (also called principalcomponents))
- 2009-11-11 08:07:04下载
- 积分：1
