-- LAPACK routine (version 3.1) --
             Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd..
             November 2006
             Purpose
             =======
             
             DBDSDC computes the singular value decomposition (SVD) of a real
             N-by-N (upper or lower) bidiagonal matrix B:  B = U * S * VT,
             using a divide and conquer method, where S is a diagonal matrix
             with non-negative diagonal elements (the singular values of B), and
             U and VT are orthogonal matrices of left and right singular vectors,
             respectively. DBDSDC can be used to compute all singular values,
             and optionally, singular vectors or singular vectors in compact form.
             
             This code makes very mild assumptions about floating point
             arithmetic. It will work on machines with a guard digit in
             add/subtract, or on those binary machines without guard digits
             which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
             It could conceivably fail on hexadecimal or decimal machines
             without guard digits, but we know of none.  See DLASD3 for details.
             
             The code currently calls DLASDQ if singular values only are desired.
             However, it can be slightly modified to compute singular values
             using the divide and conquer method.
             
            
 Inheritance Hierarchy
Inheritance Hierarchy DWSIM.MathOps.DotNumerics (in DWSIM.MathOps.DotNumerics.dll) Version: 1.0.0.0 (1.0.0.0)
 Syntax
SyntaxThe DBDSDC type exposes the following members.
 Constructors
Constructors|  | Name | Description | 
|---|
|  | DBDSDC |  | 
|  | DBDSDC(LSAME, ILAENV, DLAMCH, DLANST, DCOPY, DLARTG, DLASCL, DLASD0, DLASDA, DLASDQ, DLASET, DLASR, DSWAP, XERBLA) |  | 
Top Methods
Methods|  | Name | Description | 
|---|
|  | Run | Purpose
             =======
             
             DBDSDC computes the singular value decomposition (SVD) of a real
             N-by-N (upper or lower) bidiagonal matrix B:  B = U * S * VT,
             using a divide and conquer method, where S is a diagonal matrix
             with non-negative diagonal elements (the singular values of B), and
             U and VT are orthogonal matrices of left and right singular vectors,
             respectively. DBDSDC can be used to compute all singular values,
             and optionally, singular vectors or singular vectors in compact form.
             
             This code makes very mild assumptions about floating point
             arithmetic. It will work on machines with a guard digit in
             add/subtract, or on those binary machines without guard digits
             which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
             It could conceivably fail on hexadecimal or decimal machines
             without guard digits, but we know of none.  See DLASD3 for details.
             
             The code currently calls DLASDQ if singular values only are desired.
             However, it can be slightly modified to compute singular values
             using the divide and conquer method. | 
Top Fields
Fields Extension Methods
Extension Methods See Also
See Also