Linear and multilinear algebra; matrix theory Proof
Proof of the existence of an orthonormal basis by the Gram–Schmidt process
Builds on Inner productNorm induced by an inner productOrthonormal familyOrthonormal basisAn orthonormal family is linearly independentEvery linearly independent set extends to a basisDimension theorem for vector spacesGram–Schmidt processGram–Schmidt vectors are orthogonalLinearly independent set of the right size is a basisLinear span
Proof
We first prove the extension statement. The existence then follows by extending the empty family.
- Let be an inner product space over or of finite dimension , with inner product and induced norm .
- Let be an orthonormal family in . Its vectors are distinct, since for .
- The family is linearly independent. So its set of vectors extends to a basis of .
- All bases of have the same cardinality, so has elements. Hence the family is finite. Write it with .
- List as with for . Let be the vectors of the Gram–Schmidt process applied to .
- We show for , by induction on . First, .
- Let and assume for . Then , because for .
- By the properties of the Gram–Schmidt vectors, are nonzero and pairwise orthogonal. Also .
- Set , which is defined since . Then .
- For , , since is real. So is an orthonormal family.
- For , , since .
- The family is linearly independent by step 10 and the same result as in step 3. It has vectors, so it is a basis of .
- So is an orthonormal basis of that extends . This proves the second claim.
- The empty family is orthonormal, because the condition on pairs is vacuous. Applying step 13 to it gives an orthonormal basis of . This proves the first claim.
Idea
Extend the orthonormal family to any basis, then run Gram–Schmidt and normalise. The process leaves the first vectors alone, because they are already orthogonal unit vectors. The output is orthonormal, hence independent, and has the right number of vectors to be a basis.
Reading path
To understand this page from the ground up, read these 59 pages in order. The foundations come first. The path takes the proofs Proof of the Steinitz exchange lemma by induction, Proof that the Gram–Schmidt vectors are orthogonal, Proof that an orthonormal family is linearly independent, Proof that every linearly independent set extends to a basis, by Zorn's lemma, Proof of Zorn's lemma, Proof that n independent or n spanning vectors in an n-dimensional space form a basis.
- Element definition
- Proof of Zorn's lemma proof
- Proposition concept
- Vector space definition
- Set definition
- Disjunction definition
- Implication definition
- Predicate definition
- Inner product definition
- Linear combination definition
- Linear subspace definition
- Norm definition
- Family of sets definition
- Ordered pair definition
- Union definition
- Existential quantifier definition
- Universal quantifier definition
- Inner product space definition
- Orthogonal vectors definition
- Linear independence definition
- Linear span definition
- Cartesian product definition
- Subset definition
- Union of a family of sets definition
- Uniqueness quantifier definition
- Norm induced by an inner product definition
- Orthonormal family definition
- Spanning set definition
- Binary relation definition
- Proof that an orthonormal family is linearly independent proof
- Finite-dimensional vector space definition
- Basis definition
- Gram–Schmidt process concept
- Proof of the Steinitz exchange lemma by induction proof
- Antisymmetric relation definition
- Reflexive relation definition
- Transitive relation definition
- Function definition
- Dimension definition
- Dimension theorem for vector spaces statement
- Orthonormal basis definition
- An orthonormal family is linearly independent statement
- Proof that the Gram–Schmidt vectors are orthogonal proof
- Steinitz exchange lemma statement
- Preorder definition
- Choice function definition
- Gram–Schmidt vectors are orthogonal statement
- Proof that n independent or n spanning vectors in an n-dimensional space form a basis proof
- Partial order definition
- Axiom of choice statement
- Linearly independent set of the right size is a basis statement
- Maximal element definition
- Total order definition
- Upper bound definition
- Chain definition
- Zorn's lemma statement
- Proof that every linearly independent set extends to a basis, by Zorn's lemma proof
- Every linearly independent set extends to a basis statement
- Proof of the existence of an orthonormal basis by the Gram–Schmidt process proof
Where this leads
117 pages build on this one.
- Singular value decomposition
- Reflection
- Spectral theorem for normal matrices
- Riesz representation theorem in finite dimensions
- Spectral theorem
- Side-side-side congruence
- Least squares
- Spectral theorem for Hermitian matrices
- Dimension of the orthogonal complement
- QR decomposition
- Polar decomposition
- Orthogonal projection is the closest point
- Angle-angle similarity
- Principal axis theorem
- Orthogonal complement of the orthogonal complement
- Orthogonal projection
- A space is the direct sum of a subspace and its orthogonal complement
- Cartan–Dieudonné theorem
- Existence of an orthonormal basis
- Earthquake location problem
- Spectral theorem for unbounded self-adjoint operators
- Non-negative least squares
- Proof of the principal axis theorem from the spectral theorem
- Hellinger–Reissner principle
- Conjugate residual method
- Full waveform inversion
- Local regression
- Geophysical inversion
- Proof of the singular value decomposition from the spectral theorem
- Quantum Zeno effect
- Hilbert–Schmidt expansion theorem
- Minimal residual method
- Toeplitz operator
- Moving horizon estimation
- Céa's lemma
- Bilinear series of a symmetric kernel
- Ordinary least squares
- QR algorithm
- Proof that the orthogonal projection is the closest point
- Smoothing spline
- Proof of side-side-side congruence with orthonormal frames
- Proof of the Riesz representation theorem in finite dimensions
- Finite element method in structural mechanics
- Lax–Milgram theorem
- Uhlmann's theorem
- Response surface methodology
- Nonlinear regression
- Spectral theorem for compact self-adjoint operators
- Courant–Fischer characterization of characteristic values
- Generalized minimal residual method
- Minimum total potential energy principle
- Proof of the spectral theorem for self-adjoint operators by induction on the dimension
- Data assimilation
- Principle of material frame-indifference
- Proof of the Cartan–Dieudonné theorem by induction on the dimension
- Mixed state
- Purification of a quantum state
- Gleason's theorem
- Gauss–Newton algorithm
- Hilbert space adjoint
- Stone's theorem on one-parameter unitary groups
- Lidskii's trace formula for integral operators
- Hamiltonian operator
- Second quantization
- Proof that the orthogonal complement of the orthogonal complement is the subspace
- Spectrum of the Laplace–Beltrami operator
- Principal stresses
- Hilbert projection theorem
- Wick rotation
- Eckart–Young theorem
- Proof of the formula for the dimension of the orthogonal complement
- Strang splitting
- Korn's inequality
- Ridge regression
- L-curve
- Lie–Trotter product formula
- Proof of the polar decomposition from the singular value decomposition
- Biconjugate gradient stabilized method
- Born rule
- Borel functional calculus
- Galerkin method
- GNSS positioning
- System identification
- Schmidt decomposition
- Operator monotone function
- Proof of the spectral theorem for normal matrices by deflation
- Empirical risk minimization
- Isotonic regression
- Projection body
- Mercer's theorem
- Proof of the spectral theorem for Hermitian matrices
- Bra–ket notation
- Quantum computing
- Wave function collapse
- Principal component analysis
- Proof of angle-angle similarity with the law of sines
- Hu–Washizu principle
- Inertia tensor and principal axes
- Bidiagonalization
- Ladyzhenskaya–Babuška–Brezzi condition
- Proof that a space is the direct sum of a finite-dimensional subspace and its orthogonal complement
- Levenberg–Marquardt algorithm
- Schur product theorem
- Riesz representation theorem
- Box–Jenkins method
- Singular values of a compact operator
- Lasso
- Householder transformation
- Numerical methods for linear least squares
- Observable
- Schmidt's singular value decomposition of a kernel
- Polar decomposition of the deformation gradient
- Spectral theorem for bounded normal operators
- Hidden-variable theory
- Channel capacity of a quantum channel
- Lomb–Scargle periodogram
- Proof of the QR decomposition by clearing the first column
Further reading
- Web https://linear.axler.net/LADR4e.pdf, Theorems 6.35 and 6.36
About this page
| Tag | 6G6ZHPR66X |
|---|---|
| URI | m2://6G6ZHPR66X |
| Kind | proof |
| Writing | W0 stub |
| MSC | 15A63, 46C05 |
| Proves | Existence of an orthonormal basis |
| Uses | Inner product, Norm induced by an inner product, Orthonormal family, Orthonormal basis, An orthonormal family is linearly independent, Every linearly independent set extends to a basis, Dimension theorem for vector spaces, Gram–Schmidt process, Gram–Schmidt vectors are orthogonal, Linearly independent set of the right size is a basis, Linear span |
| Changed | 4 November 2026 |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
No page links to this page yet.