Linear and multilinear algebra; matrix theory Proof
Proof that an orthonormal family is linearly independent
Builds on Inner productOrthonormal familyLinear independence
Proof
We take the inner product of a vanishing combination with each vector of the family.
- Let be an inner product space over or , with inner product . Let be an orthonormal family in , so for all .
- By the definition of linear independence of a family, it is enough to show that each finite subfamily is linearly independent.
- Let be distinct indices in . Let with .
- Fix with . The inner product of with is , by linearity in the first argument.
- Linearity in the first argument also gives .
- Since the indices are distinct, . So the sum in step 5 equals .
- By steps 3, 4 and 5, this sum is also . Hence .
- This holds for each , so the only vanishing combination is the trivial one. Thus is linearly independent.
Idea
The inner product with picks out the coefficient of in a combination, because all the other vectors are orthogonal to and has length one. If the combination is zero, each picked coefficient is zero.
Reading path
To understand this page from the ground up, read these 7 pages in order. The foundations come first.
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- Vector space definition
- Inner product definition
- Linear combination definition
- Orthogonal vectors definition
- Linear independence definition
- Orthonormal family definition
- Proof that an orthonormal family is linearly independent proof
Where this leads
121 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
- An orthonormal family is linearly independent
- Orthogonal projection is the closest point
- Angle-angle similarity
- Classification of isometries of the plane
- 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
- Proof of the existence of an orthonormal basis by the Gram–Schmidt process
- 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
- Proof of the classification of isometries of the plane
- Lomb–Scargle periodogram
- Proof of the QR decomposition by clearing the first column
Further reading
- Web https://linear.axler.net/LADR4e.pdf, Corollary 6.25
About this page
| Tag | HP32FXA1ZG |
|---|---|
| URI | m2://HP32FXA1ZG |
| Kind | proof |
| Writing | W0 stub |
| MSC | 15A63, 46C05 |
| Proves | An orthonormal family is linearly independent |
| Uses | Inner product, Orthonormal family, Linear independence |
| Changed | 4 November 2026 |
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