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For equal finite-dimensional closed subspaces of a Hilbert space $T,S$, positivity of $\cos {\theta }_{T,S}$ makes $P_S{|}_T$ invertible. The displayed reconstruction is the unique element of $T$ whose orthogonal projection onto $S$ matches that of $f$. It is the oblique projection onto $T$ along $S^{\perp }$. Its operator norm is the value of the secant function at the directed subspace angle, and its error is at most that secant function value times the best orthogonal projection error. The lower error bound follows from the Pythagorean identity. Zero-dimensional cases are handled directly.

Interpret the angle as the directed subspace angle defined by the infimum of projected unit vectors; it is different from the smallest angle between two subspaces. WriteConsider the bounded linear operator $T:W⟶V^{\perp }$ given by $Tw=P_{V^{\perp }}w$. Its adjoint operator, between these two Hilbert spaces, is $T^{\ast }u=P_{W}u$: for $w\in W$ and $u\in V^{\perp }$, the orthogonal projections give $⟨Tw,u⟩=⟨w,u⟩=⟨w,P_{W}u⟩$. The two positive directed subspace angle cosines yieldThe first bound makes $T$ injective and gives a closed range. Explicitly, if $T{w}_j$ converges, then $\Vert w_j-w_k\Vert \le a^{-1}\Vert T{w}_j-T{w}_k\Vert$, so $(w_j)$ is a Cauchy sequence. The closed subspace of a Hilbert space $W$ is complete, and its limit maps to the proposed range limit. The second bound gives $\ker T^{\ast }=\{0\}$. A vector $u\in V^{\perp }$ orthogonal to the range has $T^{\ast }u=0$, so it must be zero. The range is therefore dense as well as closed in $V^{\perp }$, and $T$ is onto. This is the mechanism of invertibility from lower bounds on an operator and its adjoint.

For any $f\in H$, choose the unique $w\in W$ with $Tw=P_{V^{\perp }}f$. Then $P_{V^{\perp }}(f-w)=0$, so $f-w\in V$. Moreover, if $w\in W\cap V$, then $Tw=0$ and hence $w=0$. Every vector has a unique decomposition, andThe direct sum is a topological one as well: the component $w=T^{-1}{P}_{V^{\perp }}f$ depends boundedly on $f$, with operator norm at most $a^{-1}$.

For precision, the quoted equality of the norms of complementary oblique projections needs both summands nonzero. For example, with $H=\mathbb{R}$, $V=H$ and $W=\{0\}$, the oblique projection is $I$, so $\Vert I\Vert =1$ but $\Vert I-I\Vert =0$. The secant function has value one here, so the second equality in the quoted formula fails. With nonzero complementary summands its intended version is valid. The proof above does not use that formula. The angle itself is undefined on a zero source space because it has no unit vectors; expressing the hypotheses as the two lower bounds handles zero spaces without ambiguity.

The linear independence of the first $n$ elements of each orthonormal system shows that $T_n$ and $S_n$ have the same finite dimension $n$ and are closed subspaces of a Hilbert space. Apply part (b) with $U=T_n$ and $V=S_n^{\perp }$. Since $(S_n^{\perp }{)}^{\perp }=S_n$, the positive directed subspace angle cosine givesLet $Q$ be the oblique projection onto $T_n$ along $S_n^{\perp }$. Define ${\tilde{f}}_n=Qf$. Its residual $f-Qf$ is orthogonal to every ${\psi }_j$ with $1\le j\le n$, so the required measurements agree. Conversely, if $g\in T_n$ has the same measurements, then $f-g\in S_n^{\perp }$; uniqueness of the direct sum decomposition gives $g=Qf$. Thus this is finite-dimensional Hilbert sampling reconstruction.

There is also an explicit coefficient description. Use the inner product convention linear in its first entry and putThen $Cc=b$. The orthonormal systems show $\Vert P_{S_n}{\sum }_k{c}_k{\varphi }_k\Vert =\Vert Cc{\Vert }_2$ and $\Vert {\sum }_k{c}_k{\varphi }_k\Vert =\Vert c{\Vert }_2$, so the smallest singular value of $C$ is $\cos {\theta }_{T_n,S_n}>0$. Hence $c=C^{-1}b$, another direct proof of existence and uniqueness.

For $n\ge 1$, both summands of this direct sum are nonzero: the infinite orthonormal system $({\psi }_j)$ contains ${\psi }_{n+1}\in S_n^{\perp }$. The permitted oblique projection norm formula therefore applies without its degenerate exception, givingThe operator norm immediately yields the stability estimate $\Vert {\tilde{f}}_n\Vert \le \sec {\theta }_{T_n,S_n}\Vert f\Vert$. For the approximation bounds, put $e=f-P_{T_n}f$. Because $Q$ fixes $T_n$, we haveso the operator norm estimate gives $\Vert f-Qf\Vert \le \sec {\theta }_{T_n,S_n}\Vert e\Vert$. For the lower bound, $e\perp T_n$ while $P_{T_n}f-Qf\in T_n$. The Pythagorean identity givesThe unique measurement-matching reconstruction is stable and within the secant function factor of the best orthogonal projection approximation:If a zero-dimensional reconstruction is admitted, it is simply ${\tilde{f}}_0=0$ and its error equals the norm of $f$; that case is best stated directly instead of using the angle of a zero space.