Difference between revisions of "ApCoCoA-1:Num.SVD"
From ApCoCoAWiki
(Updated example. Use Dec to display result.) |
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| Line 14: | Line 14: | ||
<example> | <example> | ||
| − | D:= | + | D:=[[1,2,7,18],[2,4,9,12],[23,8,9,10]]; |
| − | Num.SVD(D); | + | Dec(Num.SVD(D),3); |
| + | |||
| + | -- CoCoAServer: computing Cpu Time = 0 | ||
------------------------------- | ------------------------------- | ||
[Mat([ | [Mat([ | ||
| − | [- | + | [<quote>-0.473</quote>, <quote>-0.666</quote>, <quote>-0.575</quote>], |
| − | [- | + | [<quote>-0.415</quote>, <quote>-0.407</quote>, <quote>0.813</quote>], |
| − | + | [<quote>-0.776</quote>, <quote>0.624</quote>, <quote>-0.084</quote>] | |
| − | [- | ||
]), Mat([ | ]), Mat([ | ||
| − | [ | + | [<quote>33.091</quote>, <quote>17.047</quote>, <quote>3.365</quote>] |
]), Mat([ | ]), Mat([ | ||
| − | [- | + | [<quote>-0.579</quote>, <quote>-0.266</quote>, <quote>-0.424</quote>, <quote>-0.642</quote>], |
| − | [- | + | [<quote>0.755</quote>, <quote>0.119</quote>, <quote>-0.159</quote>, <quote>-0.624</quote>], |
| − | [- | + | [<quote>-0.265</quote>, <quote>0.423</quote>, <quote>0.750</quote>, <quote>-0.431</quote>], |
| + | [<quote>-0.153</quote>, <quote>0.857</quote>, <quote>-0.480</quote>, <quote>0.100</quote>] | ||
])] | ])] | ||
------------------------------- | ------------------------------- | ||
Revision as of 08:08, 7 July 2009
Num.SVD
Computes the singular value decomposition of a matrix.
Syntax
Num.SVD(A:MAT):[U:MAT,S:MAT,VT:MAT]
Description
Please note: The function(s) explained on this page is/are using the ApCoCoAServer. You will have to start the ApCoCoAServer in order to use it/them.
@param A The matrix we want to decompose.
@return This function returns a list of three matrices which form the singular value decomposition of the input matrix. The list produced is [U, S, VT].
Example
D:=[[1,2,7,18],[2,4,9,12],[23,8,9,10]]; Dec(Num.SVD(D),3); -- CoCoAServer: computing Cpu Time = 0 ------------------------------- [Mat([ [<quote>-0.473</quote>, <quote>-0.666</quote>, <quote>-0.575</quote>], [<quote>-0.415</quote>, <quote>-0.407</quote>, <quote>0.813</quote>], [<quote>-0.776</quote>, <quote>0.624</quote>, <quote>-0.084</quote>] ]), Mat([ [<quote>33.091</quote>, <quote>17.047</quote>, <quote>3.365</quote>] ]), Mat([ [<quote>-0.579</quote>, <quote>-0.266</quote>, <quote>-0.424</quote>, <quote>-0.642</quote>], [<quote>0.755</quote>, <quote>0.119</quote>, <quote>-0.159</quote>, <quote>-0.624</quote>], [<quote>-0.265</quote>, <quote>0.423</quote>, <quote>0.750</quote>, <quote>-0.431</quote>], [<quote>-0.153</quote>, <quote>0.857</quote>, <quote>-0.480</quote>, <quote>0.100</quote>] ])] -------------------------------
See also
