Method on @sym: S = svd (A) ¶

Method on @sym: [U, S, V] = svd (A) ¶

Symbolic singular value decomposition.

The SVD: U*S*V’ = A

Singular values example:

A = sym([1 0; 3 0]);
svd(A)
  ⇒ (sym 2×1 matrix)

      ⎡√10⎤
      ⎢   ⎥
      ⎣ 0 ⎦

FIXME: currently only singular values, not singular vectors. Should add full SVD to sympy.

See also: svd, @@sym/eig.

Package: symbolic