qr方法求赫申伯格矩陣的全部特征值
上傳時間： 2015-02-13
上傳用戶：縹緲
QR ALGORITHM To obtain the eigenvalues of a symmetric, tridiagonal n by n matrix
標(biāo)簽： eigenvalues tridiagonal ALGORITHM symmetric
上傳時間： 2014-01-15
上傳用戶：凌云御清風(fēng)
工會會員信息管理系統(tǒng) v1.0.5 (DAO+ACCESS+QR).
標(biāo)簽： ACCESS DAO QR 信息管理系統(tǒng)
上傳時間： 2014-01-15
上傳用戶：wanqunsheng
Common Martix Operation ,include transpose, qr-factorization, trangular martix
標(biāo)簽： qr-factorization Operation transpose trangular
上傳時間： 2013-11-30
上傳用戶：xc216
MATLAB, computing matrix by QR
標(biāo)簽： computing MATLAB matrix by
上傳時間： 2015-05-05
上傳用戶：頂?shù)弥?/p>
The module LSQ is for unconstrained linear least-squares fitting. It is based upon Applied Statistics algorithm AS 274 (see comments at the start of the module). A planar-rotation algorithm is used to update the QR- factorization. This makes it suitable for updating regressions as more data become available. The module contains a test for singularities which is simpler and quicker than calculating the singular-value decomposition. An important feature of the algorithm is that it does not square the condition number. The matrix X X is not formed. Hence it is suitable for ill- conditioned problems, such as fitting polynomials. By taking advantage of the MODULE facility, it has been possible to remove many of the arguments to routines. Apart from the new function VARPRD, and a back-substitution routine BKSUB2 which it calls, the routines behave as in AS 274.
標(biāo)簽： least-squares unconstrained Statisti Applied
上傳時間： 2015-05-14
上傳用戶：aig85
基于矩陣QR分解的最小二乘擬合MATLAB源程序
上傳時間： 2015-06-05
上傳用戶：ljt101007
利用隱式QR方法求一個實矩陣全部特征值和特征向量的通用子程序。
上傳時間： 2015-06-19
上傳用戶：wang5829
empirical mode decomposition(EMD)分解算法的matlab代碼
標(biāo)簽： decomposition empirical matlab mode
上傳時間： 2013-11-28
上傳用戶：小眼睛LSL
通過奇異值分解實現(xiàn)的最小二乘擬合算法 inear least-squares fit by singular value decomposition
標(biāo)簽： decomposition least-squares singular inear
上傳時間： 2015-07-26
上傳用戶：bibirnovis
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