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Bessel's inequality for a finite orthonormal list and Parseval's identity for an orthonormal basis
Statement
If is a finite orthonormal list and is any vector, then
Equality holds exactly when . If the list is an orthonormal basis, then for all ,
and
The empty-list case is included.
Facts & Assumptions
Given: A finite orthonormal list and vectors .
Orthonormality gives for and (Orthogonal vectors and subspaces, orthogonal and orthonormal sets, and orthonormal bases).
Orthogonal vectors satisfy the Pythagorean identity (Pythagoras, the parallelogram identity, and the real and complex polarisation identities).
, the set of finite linear combinations of elements of ( is exactly the set of linear combinations of finite lists of elements of , and ).
Finite sums include the empty sum, whose additive value is zero (The product of a finite list in a monoid, by recursion, with the empty product () equal to the identity).
Proof
Put . For each , [L1] gives , so is orthogonal to .
By [L2], . A second use of orthonormality gives , proving Bessel's inequality.
Equality holds in step 2.1 exactly when , hence exactly when . By [L3], this is exactly belonging to the listed span.
If the list is a basis, its span is , so step 3.1 gives the coordinate expansion and the squared-length identity. Substitute the coordinate expansion of into and use conjugate symmetry to obtain the displayed inner-product formula.
When , [L4] makes every displayed sum zero; the list can be a basis only of the zero space, so all assertions remain valid.
Depends on
- Orthogonal vectors and subspaces, orthogonal and orthonormal sets, and orthonormal bases
- Pythagoras, the parallelogram identity, and the real and complex polarisation identities
- The product $g_0 g_1 \cdots g_{n-1}$ of a finite list in a monoid, by recursion, with the empty product ($n = 0$) equal to the identity
- $\operatorname{span}(S)$ is exactly the set of linear combinations of finite lists of elements of $S$, and $\operatorname{span}(\varnothing) = \{0_V\}$
Used by
- Bessel's inequality is strict for a vector outside the span of a proper orthonormal set Example
- Orthogonal projection is linear, and an orthonormal basis (eᵢ) of W gives P_Wv=∑ᵢ⟨ v,eᵢ⟩ eᵢ Proposition
- Finite-dimensional Riesz representation: every functional is uniquely v↦⟨ v,w⟩ Theorem
- In orthonormal bases, the matrix of the adjoint is the conjugate transpose of the matrix Theorem
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 49 results over 20 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Sheldon Axler, Linear Algebra Done Right, 4th ed., results 6.24, 6.26, and 6.30 (standard reference, not scraped)