9 Orthogonal Complement and Decomposition
Orthogonal Complement
For a subset \mathcal{M} of an inner-product space \mathcal{V}, the orthogonal complement \mathcal{M}^{\perp} of \mathcal{M} is defined to be the set of all vectors in \mathcal{V} that are orthogonal to every vector in \mathcal{M}
\mathcal{M}^{\perp} = \left\{ x \in \mathcal{V} \mid \langle x, m \rangle = 0, \forall m \in \mathcal{M} \right\}.
The set \mathcal{M}^{\perp} is a subspace even if \mathcal{M} is not.
Orthogonal Complementary Subspaces
When \mathcal{M} is a subspace of a finite-dimensional inner-product space \mathcal{V}, \mathcal{M} and \mathcal{M}^{\perp} are complementary subspaces in \mathcal{V}
\mathcal{V} = \mathcal{M} \oplus \mathcal{M}^{\perp}.
Properties of orthogonal complementary subspaces
Suppose \mathcal{M} is a subspace of an n-dimensional inner-product space \mathcal{V}.
\text{dim} (\mathcal{M}) + \text{dim} (\mathcal{M}^{\perp}) = n
\mathcal{M}^{\perp^{\perp}} = \mathcal{M}.
Orthogonal Decomposition
For every \mathbf{A} \in \mathbb{R}^{m \times n},
R (\mathbf{A}) \perp N (\mathbf{A}^{H}),
N (\mathbf{A}) \perp R (\mathbf{A}^{H}),
which means that every matrix \mathbf{A} \in \mathbb{R}^{m \times n} produces an orthogonal decomposition of \mathbb{R}^{m} and \mathbb{R}^{n} in the sense that
\mathbb{R}^{m} = R (\mathbf{A}) \oplus R (\mathbf{A})^{\perp} = R (\mathbf{A}) \oplus N (\mathbf{A}^{H}),
\mathbb{R}^{n} = N (\mathbf{A}) \oplus N (\mathbf{A})^{\perp} = N (\mathbf{A}) \oplus R (\mathbf{A}^{H}).