Linear and multilinear algebra; matrix theory Definition
Inner product
Builds on Vector space
Definition
Let be or , and let be a vector space over . An inner product on is a map such that, for all and :
- .
- .
- if .
Remarks
Over , the conjugation does nothing, so an inner product is a symmetric positive definite bilinear form. Over , conditions 1 and 2 give , so the map is conjugate linear in the second argument. Many physicists, and Mathlib, use the opposite convention: linear in the second argument. The dot product on and on are inner products.
Reading path
To understand this page from the ground up, read these 2 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Vector space definition
- Inner product definition
Where this leads
102 pages build on this one.
- Inner product space
- Reflection
- Parallelogram law
- Parseval's identity
- Riesz representation theorem in finite dimensions
- Polarisation identity
- Spectral theorem
- Orthogonal complement
- Coordinates in an orthonormal basis
- Orthonormal family
- Pythagorean theorem in an inner product space
- Least squares
- Eigenvalues of a self-adjoint operator are real
- Matrix of the adjoint is the conjugate transpose
- Spectral theorem for Hermitian matrices
- Dimension of the orthogonal complement
- Normal operator
- QR decomposition
- Orthonormal basis
- Gram matrix
- Eigenspaces of a self-adjoint operator are orthogonal
- An orthonormal family is linearly independent
- Norm induced by an inner product
- Self-adjoint operator
- Orthogonal projection is the closest point
- Principal axis theorem
- Orthogonal complement of the orthogonal complement
- Orthogonal projection
- A linear isometry preserves the inner product
- Bessel's inequality
- Cauchy–Schwarz inequality
- A space is the direct sum of a subspace and its orthogonal complement
- Adjoint of a linear map
- Orthogonal vectors
- Cartan–Dieudonné theorem
- Gram–Schmidt process
- Gram–Schmidt vectors are orthogonal
- Existence of an orthonormal basis
- Non-negative least squares
- Derivation of the conjugate gradient method
- Clarkson's inequalities
- Paley–Zygmund inequality
- Conjugate residual method
- Local regression
- Hilbert–Schmidt expansion theorem
- Minimal residual method
- Toeplitz operator
- Partial isometry
- Importance sampling
- Céa's lemma
- Bilinear series of a symmetric kernel
- Ordinary least squares
- QR algorithm
- Smoothing spline
- Lax–Milgram theorem
- Principal curvature
- Shape operator
- Hadamard's inequality in Fredholm theory
- 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
- Hadamard's inequality
- Arnoldi iteration
- Gauss–Newton algorithm
- Hilbert space adjoint
- Heisenberg inequality for the Fourier transform
- Lidskii's trace formula for integral operators
- Normal coordinates
- Hadamard's maximal determinant problem
- Spectrum of the Laplace–Beltrami operator
- Hilbert projection theorem
- Ridge regression
- L-curve
- Biconjugate gradient stabilized method
- Galerkin method
- Bernstein's theorem on absolutely convergent Fourier series
- Operator monotone function
- Least squares approximation
- Empirical risk minimization
- Isotonic regression
- Projection body
- Mercer's theorem
- Positive definiteness of the energy
- Principal component analysis
- Ladyzhenskaya–Babuška–Brezzi condition
- Levenberg–Marquardt algorithm
- Schur product theorem
- Fundamental theorem of space curves
- Riesz representation theorem
- Box–Jenkins method
- Singular values of a compact operator
- Lasso
- Householder transformation
- Numerical methods for linear least squares
- Schmidt's singular value decomposition of a kernel
- Nesbitt's inequality
- Three-term recurrence for orthogonal polynomials
- Bareiss algorithm
- Frenet–Serret formulas
Further reading
About this page
| Tag | 0VGSYBWHV2 |
|---|---|
| URI | m2://0VGSYBWHV2 |
| Kind | definition |
| Writing | W1 stated |
| MSC | 15A63, 46C05 |
| Defines | Inner product |
| Uses | Vector space |
Markdown · JSON · Edit on GitHub
What this page needs for W2
- edge instance_of in: one example (0 of 1)
- edge not_instance_of in: one non-example that fails one clause (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.