Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
bdiag
block diagonalization, generalized eigenvectors
Syntax
[Ab [,X [,bs]]]=bdiag(A [,rmax])
Arguments
- A
 real or complex square matrix
- rmax
 real number
- Ab
 real or complex square matrix
- X
 real or complex non-singular matrix
- bs
 vector of integers
Description
[Ab [,X [,bs]]]=bdiag(A [,rmax])
performs the block-diagonalization of matrix A.  bs
            gives the structure of the blocks (respective sizes of the
            blocks).  X is the change of basis i.e
            Ab = inv(X)*A*Xis block diagonal.
rmax controls the conditioning of X; the
            default value is the l1 norm of A.
To get a diagonal form (if it exists) choose a large value for
            rmax (rmax=1/%eps for example).
            Generically (for real random A) the blocks are (1x1) and (2x2) and
            X is the matrix of eigenvectors.
Examples
//Real case: 1x1 and 2x2 blocks a=rand(5,5);[ab,x,bs]=bdiag(a);ab //Complex case: complex 1x1 blocks [ab,x,bs]=bdiag(a+%i*0);ab
See also
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