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data_nihe
曲线拟合的最小二乘法要解决的问题，实际上就是求以下超定方程组的最小二乘解的问题。(Least squares curve fitting to solve the problem, in fact, find the following overdetermined least squares solution for the problem group.)
- 2021-03-02 21:09:33下载
- 积分：1
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regrRR
Ridge Regression RR 岭回归估计，是非常有用的非线性时间序列算法，在局部多项式预测中非常有用。(Ridge Regression RR ridge regression estimates, it is useful to nonlinear time series algorithms, in Local Polynomial prediction in very useful.)
- 2008-07-24 15:50:34下载
- 积分：1
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f77_gcc
PSCAD interface with C
- 2012-08-06 08:14:51下载
- 积分：1
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code
用C++编写的大整数计算的模板，可实现加、减、乘、除、取模等运算，可以通过此源码学习高精度的实现。(Written with C++ template large integer can be realized addition, subtraction, multiplication, division, modulus and other operations, you can achieve high-precision study of this source.)
- 2011-06-05 17:19:32下载
- 积分：1
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search
这是一个数组练习，程序的作用是查询一个一维数组（数值型数组）中每一个元素出现的次数，且元素出现的顺序不能改变(This is an array of exercises, the program' s role is to query a one-dimensional array (numeric array) in the number of occurrences of each element, and the element can not be changed in order of appearance)
- 2013-07-26 09:37:09下载
- 积分：1
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shiweidele
施威德勒球壳在ansys中的建模分析，APDL语言(Of Schwedler shell modeling in ansys, APDL language)
- 2012-10-22 14:32:47下载
- 积分：1
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数字信号处理上机作业
说明： 数字信号处理DSP中，DFT离散傅里叶变换等上机作业。(In digital signal processing DSP, DFT discrete Fourier transform.)
- 2020-05-10 20:54:48下载
- 积分：1
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2DPCA.m.tar
经典的人脸识别算法：2Dpca的实现，matlab实现环境。(Classical face recognition algorithms: 2Dpca the realization)
- 2009-02-12 12:52:03下载
- 积分：1
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地震记录的数据 record
地震记录的数据，可以用来绘制地震记录，也可以作为地震反演的数据(Seismic wave inverse time migration program can realize the inversion of seismic wave)
- 2017-09-23 11:04:28下载
- 积分：1
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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
