Functions of a Matrix - GNU Octave
Description: GNU Octave

Next: Specialized Solvers, Previous: Matrix Factorizations, Up: Linear Algebra

### 18.4 Functions of a Matrix

— Function File: expm (A)

> Return the exponential of a matrix, defined as the infinite Taylor series

>               expm(A) = I + A + A^2/2! + A^3/3! + ...

> The Taylor series is not the way to compute the matrix exponential; see Moler and Van Loan, Nineteen Dubious Ways to Compute the Exponential of a Matrix, SIAM Review, 1978. This routine uses Ward's diagonal Padé approximation method with three step preconditioning (SIAM Journal on Numerical Analysis, 1977). Diagonal Padé approximations are rational polynomials of matrices

>                    -1
>               D (A)   N (A)

> whose Taylor series matches the first `2q+1` terms of the Taylor series above; direct evaluation of the Taylor series (with the same preconditioning steps) may be desirable in lieu of the Padé approximation when `Dq(A)` is ill-conditioned.

> See also: logm, sqrtm.

— Function File: s = logm (A)
— Function File: s = logm (A, opt_iters)
— Function File: [s, iters] = logm (...)

> Compute the matrix logarithm of the square matrix A. The implementation utilizes a Padé approximant and the identity

>               logm(A) = 2^k * logm(A^(1 / 2^k))

> The optional argument opt_iters is the maximum number of square roots to compute and defaults to 100. The optional output iters is the number of square roots actually computed.

> See also: expm, sqrtm.

— Loadable Function: s = sqrtm (A)
— Loadable Function: [s, error_estimate] = sqrtm (A)

> Compute the matrix square root of the square matrix A.

> Ref: N.J. Higham. A New sqrtm for matlab. Numerical Analysis Report No. 336, Manchester Centre for Computational Mathematics, Manchester, England, January 1999.

> See also: expm, logm.

— Loadable Function: kron (A, B)

> Form the Kronecker product of two matrices, defined block by block as

>               x = [a(i, j) b]

> For example:

>               kron (1:4, ones (3, 1))
>                     ⇒  1  2  3  4
>                         1  2  3  4
>                         1  2  3  4

— Loadable Function: blkmm (A, B)

> Compute products of matrix blocks. The blocks are given as 2-dimensional subarrays of the arrays A, B. The size of A must have the form `[m,k,...]` and size of B must be `[k,n,...]`. The result is then of size `[m,n,...]` and is computed as follows:

>                 for i = 1:prod (size (A)(3:end))
>                   C(:,:,i) = A(:,:,i) * B(:,:,i)
>                 endfor

— Loadable Function: x = syl (A, B, C)

> Solve the Sylvester equation

>               A X + X B + C = 0

> using standard lapack subroutines. For example:

>               syl ([1, 2; 3, 4], [5, 6; 7, 8], [9, 10; 11, 12])
>                    ⇒ [ -0.50000, -0.66667; -0.66667, -0.50000 ]