Functional Analysis Lecture 15
[[lecture-data]]
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Lecture Notes: Rodriguez, page 77
3. Hilbert Spaces
Orthonormal Bases
Recall from last time, we introduced
{ e λ } λ ∈ Λ in a Hilbert space is maximal if u ∈ H and ⟨ u , e λ ⟩ = 0 for all λ ∈ Λ implies u = 0 .
see maximal orthonormal set
See separable hilbert spaces have countable maximal orthonormal sets
see orthonormal basis of a hilbert space
ie like in finite-dimensional linear algebra, we can write any element as a linear combination of the basis elements. But in this space, there might be an infinite number of such elements.
First, we prove { ∑ n = 1 m ⟨ u , e n ⟩ e n } m is Cauchy. Let ϵ > 0 . Then by Bessel's inequality , we have
You can't use 'macro parameter character #' in math mode \sum_{n=1}^\infty \lvert \langle u, e_{n} \rangle \rvert { #2 } \leq \lvert \lvert u \rvert \rvert { #2 } < \infty \sum_{n=1}^\infty \lvert \langle u, e_{n} \rangle \rvert { #2 } \leq \lvert \lvert u \rvert \rvert { #2 } < \infty Thus, for all M ∈ N such that for all N ≥ M we have ∑ m = N + 1 ∞ | ⟨ u , e n ⟩ | 2 < ϵ
Then for all m > ℓ ≥ M we compute
You can't use 'macro parameter character #' in math mode \begin{align} \left\lvert \left\lvert \sum_{n=1}^m \langle u, e_{n} \rangle e_{n} - \sum_{n=1}^\ell \langle u, e_{n} \rangle e_{n} \right\rvert \right\rvert &= \sum_{n=\ell+1}^m \lvert \langle u, e_{n} \rangle \rvert { #2 } \\ &\leq \sum_{\ell+1}^\infty \lvert \langle u, e_{n} \rangle \rvert { #2 } \\ &< \epsilon^2 \end{align} \begin{align} \left\lvert \left\lvert \sum_{n=1}^m \langle u, e_{n} \rangle e_{n} - \sum_{n=1}^\ell \langle u, e_{n} \rangle e_{n} \right\rvert \right\rvert &= \sum_{n=\ell+1}^m \lvert \langle u, e_{n} \rangle \rvert { #2 } \\ &\leq \sum_{\ell+1}^\infty \lvert \langle u, e_{n} \rangle \rvert { #2 } \\ &< \epsilon^2 \end{align} thus the sequence is indeed Cauchy. Since H is complete, there exists some u ¯ ∈ H where
u ¯ = lim m → ∞ ∑ n = 1 m ⟨ u , e n ⟩ e n By continuity of inner product , we know that for all ℓ ∈ N
⟨ u − u ¯ , e ℓ ⟩ = lim m → ∞ ⟨ u − ∑ n = 1 m ⟨ u , e n ⟩ e n , e ℓ ⟩ = lim m → ∞ [ ⟨ u , e ℓ ⟩ − ∑ n = 1 m ⟨ u , e n ⟩ ⟨ e n , e ℓ ⟩ ] = ⟨ u , e ℓ ⟩ − ⟨ u , e ℓ ⋅ 1 ⟩ = 0 Thus ⟨ u − u ¯ , e ℓ ⟩ = 0 for all ℓ if and only if u − u ¯ = 0 .
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see all elements of hilbert spaces with orthonormal bases can be written as sums of the basis elements
Thus if we have an orthonormal basis , every element can be expanded in this series in terms of the basis elements (Bessel-Fourier series). And thus every separable Hilbert space has an orthonormal basis.
Suppose { e n } is an orthonormal basis for H . Then
S = ⋃ m ∈ N { ∑ n = 1 m q n e n | q 1 , … , q m ∈ Q + i Q } is a countable. This is because elements in each component (index by m ) have a bijection with Q 2 m , which is countable. Then since the m are countable, the union is countable and therefore yields a countable set.
So by all elements of hilbert spaces with orthonormal bases can be written as sums of the basis elements , S is dense in H
(since every element u can be expanded in the series described above, and so the partial sums converge to u )
Thus for any ϵ > 0 , we have take a sufficiently long partial sum of length L to get within ϵ 2 of u and approximate each coefficient with a rational number.
So the sums will be in one of the parts of S above, ie S is a countable dense subset of H , ie H is separable.
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See Hilbert spaces with orthonormal bases are separable
Theorem (Parseval's Identity)
Let H be a Hilbert space and let { e n } be a countable orthonormal basis of H . Then for all u ∈ H ,
You can't use 'macro parameter character #' in math mode \sum_{n} \lvert \langle u, e_{n} \rangle \rvert { #2 } = \lvert \lvert u \rvert \rvert { #2 } \sum_{n} \lvert \langle u, e_{n} \rangle \rvert { #2 } = \lvert \lvert u \rvert \rvert { #2 }
(in Bessel's inequality , we only had ≤ )
We know that
u = ∑ n ⟨ u , e n ⟩ e n from all elements of hilbert spaces with orthonormal bases can be written as sums of the basis elements . If the sum over n is a finite sum, then we just expand the inner product | | u | | 2 = ⟨ u , u ⟩ . Otherwise, by continuity of inner product , we have
You can't use 'macro parameter character #' in math mode \begin{align} \lvert \lvert u \rvert \rvert { #2 } &= \lim_{ m \to \infty } \left\langle \sum_{n=1}^m \langle u, e_{n} \rangle e_{n}, \sum_{\ell=1}^m \langle u, e_{\ell} \rangle e_{\ell} \right\rangle \\ &= \lim_{ m \to \infty } \sum_{n, \ell = 1}^m\langle u, e_{n} \rangle \overline{\langle u, e_{\ell} \rangle } \langle e_{n, e_{\ell}} \rangle \\ (e_{n} \perp e_{\ell}, n \neq \ell) \implies&= \lim_{ m \to \infty } \sum_{n=1} \langle u, e_{n} \rangle \overline{\langle u, e_{n} \rangle } \\ &= \lim_{ m \to \infty } \sum_{n=1}^m \lvert \langle u, e_{n} \rangle \rvert { #2 } \begin{align} \lvert \lvert u \rvert \rvert { #2 } &= \lim_{ m \to \infty } \left\langle \sum_{n=1}^m \langle u, e_{n} \rangle e_{n}, \sum_{\ell=1}^m \langle u, e_{\ell} \rangle e_{\ell} \right\rangle \\ &= \lim_{ m \to \infty } \sum_{n, \ell = 1}^m\langle u, e_{n} \rangle \overline{\langle u, e_{\ell} \rangle } \langle e_{n, e_{\ell}} \rangle \\ (e_{n} \perp e_{\ell}, n \neq \ell) \implies&= \lim_{ m \to \infty } \sum_{n=1} \langle u, e_{n} \rangle \overline{\langle u, e_{n} \rangle } \\ &= \lim_{ m \to \infty } \sum_{n=1}^m \lvert \langle u, e_{n} \rangle \rvert { #2 }
\end{align}$$
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see Parseval's identity
We now have a way to identify every separable Hilbert space with the one that was introduced at the beginning of the course.
The finite case is easier to deal with- we can just show that they are isometrically isomorphic to C n for some n
see separable Hilbert spaces are bijective with ell-2
Fourier Series
The subset of functions { e i n x 2 π } n ∈ Z is an orthonormal subset of L 2 ( [ − π , π ] )
if we don't like working with complex exponentials we can use
e i x = cos x + i sin x And work out everything we need.
Note that
⟨ e i n x , e i m x ⟩ = ∫ − π π e i n x e i m x ― d x = ∫ − π π e i ( n − m ) x d x = { 2 π , m = n 1 i ( n − m ) e i ( n − m ) x | − π π = 0 m ≠ n Since the exponential is periodic in 2 π . Normalizing by 2 π yields
⟨ e i n x 2 π , e i m x 2 π ⟩ = { 1 m = n 0 m ≠ n Giving us our orthonormal set.
see the fourier functions form an orthonormal set
For a function f ∈ L 2 ( [ − π , π ] ) , the Fourier coefficient f ^ ( n ) of f is given by
f ^ ( n ) = 1 2 π ∫ − π π f ( t ) e − i n t d t And the N th partial Fourier sum is
S N f ( x ) = ∑ | n | ≤ N f ^ ( n ) e i n x = ∑ | n | ≤ N ⟨ f , e i n x 2 π ⟩ e i n x 2 π
see Fourier coefficient
The Fourier series of f is the formal series
∑ n ∈ Z f ^ ( n ) e i n x
see Fourier series
Does convergence (in L 2 ) ∑ n = 1 ∞ f ^ e i n x → f hold for all f ∈ L 2 ( [ − π , π ] ) ? ie, does
You can't use 'macro parameter character #' in math mode \lvert \lvert f - S_{N} f\rvert \rvert _{2} = \left( \int _{-\pi}^\pi \lvert f(x) - S_{N}f(x) \rvert { #2 } \, dx \right)^{1/2} \to {0} \, \text{ as } N \to \infty \lvert \lvert f - S_{N} f\rvert \rvert _{2} = \left( \int _{-\pi}^\pi \lvert f(x) - S_{N}f(x) \rvert { #2 } \, dx \right)^{1/2} \to {0} \, \text{ as } N \to \infty
It turns out, yes , but we will need to build some more framework to show this.
For all f ∈ L 2 ( [ − π , π ] ) and all N ∈ N ∪ { 0 } ,
S N f ( x ) = ∫ − π π D N ( x − t ) f ( t ) d x D N ( x ) = { 2 N + 1 2 π x = 0 sin ( N + 1 2 ) x 2 π sin x 2 x ≠ 0 The function D N is continuous and also smooth and is called the Dirichlet kernel .
Proof (warmup for some calculations)
For any f ∈ L 2 ( [ − π , π ] ) , we know that
S N f ( x ) = ∑ | n | ≤ N ( 1 2 π ∫ − π π f ( t ) e − i n t d t ) e i n x ( ∗ ) = ∫ − π π f ( t ) ( 1 2 π ∑ | n | ≤ N e i n ( x − t ) ) ⏟ D N ( x − t ) d t Where ( ∗ ) is by linearity of the integral
D N ( x ) = 1 2 π ∑ | n | ≤ N e i n x = 1 2 π e − i N x ∑ n = 0 2 N e i n x = { 1 2 π e − i N x [ 1 − e i ( 2 N − 1 ) x 1 − e i x ] , e i x ≠ 1 ⟺ x ≠ 0 2 N + 1 2 π , x = 0 = { 1 2 π [ e i ( N + 1 / 2 ) x − e i ( N + 1 / 2 ) x e i x / 2 − e − i x / 2 ] , x ≠ 0 2 N + 1 2 π , x = 0 ( sin x = e i x − e − i x 2 i ) ⟹ = { sin ( N + 1 2 ) x 2 π sin x 2 , x ≠ 0 2 N + 1 2 π , x = 0 Which gives us the desired result
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See fourier partial sums are given by the Dirichlet kernel
Let f ∈ L 2 ( [ − π , π ] ) . The N th Cesaro-Fourier mean of f is
σ N f ( x ) = 1 N + 1 ∑ k = 0 N S k f ( x ) Where S k f ( x ) is the k th partial Fourier sum .
see Cesaro-Fourier mean
If the Fourier coefficients are all zero, then the function is zero
Want to show that if the partial Fourier sums converge, then it must be a sum of zeros. But doing this with the S N directly is the original question.
The "averaged" version (the Cesaro-Fourier mean ) is easier to work with, so we will try and show convergence here instead
We know from real analysis that the Cesaro means of a sequence behave better but do not lose any information.
Sequences like { − 1 , 1 , − 1 , 1 , … } do not converge, but their Cersaro means do
Next time, we will see more why this convergence works.
Created 2025-07-15 ֍ Last Modified 2025-09-09