Main
Home
Quick tour
Handbook
Docs
Mailing Lists
Demonstration
Download
Sourceforge project
FAQ
Links


Toolboxes
Char
Control
Crypto
Deprecated
Engine
Finance
FunFun
General
Graphics 3D
Graphics
Image
Integration
InputOutput
JMathLib
LinearAlgebra
Matrix
Miscellaneous
Net
Polynomial
Set
Signal
SpecFun
SpecialMatrix
Statistics
String
System
Time
Trigonometric
UserInterface
...


Contact
Developers

JMathLib
A Java Clone of Octave, SciLab, Freemat and Matlab.

[Index] [Documentation] [Demonstration] [Download]

svd

Type: External

Group: matrix

Syntax

   s = svd(A) 
   [U,S,V]=svd(A)

Description

Calculates the single value decomposition of a matrix

Notes

For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an n-by-n diagonal matrix S, and an n-by-n orthogonal matrix V so that A = U*S*V'. The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >= sigma[1] >= ... >= sigma[n-1]. The singular value decompostion always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.

Examples

SVD([1,2,3;4,5,6;7,8,9]) = [16.848; 1.068; 0]

See Also

lu, qr

Last modified
sourceforge