66 relations: Aequationes Mathematicae, Algorithm, Banach space, Bounded operator, Cauchy–Schwarz inequality, Centering matrix, Characteristic polynomial, Closed graph theorem, Complete metric space, Conjugate transpose, Diagonalizable matrix, Direct sum of modules, Dot product, Dykstra's projection algorithm, Eigenvalue algorithm, Eigenvalues and eigenvectors, Frame (linear algebra), Functional analysis, Geometry, Gram–Schmidt process, Graphical projection, Hahn–Banach theorem, Hessenberg matrix, Hilbert space, Householder transformation, Idempotence, Infimum and supremum, Inner product space, Instrumental variables estimation, Invariant subspace, Kernel (linear algebra), Lattice (order), Linear algebra, Linear map, Linear regression, Linear subspace, Matrix (mathematics), Matrix multiplication, Maxima and minima, Minimal polynomial (linear algebra), Moore–Penrose inverse, Normed vector space, Oblique projection, Operator algebra, Operator K-theory, Ordinary least squares, Orthogonal complement, Orthogonality, Orthogonalization, Orthonormal basis, ..., Outer product, Partial isometry, Pavel Grinfeld, Point (geometry), QR decomposition, Riemannian geometry, Riemannian submersion, Row and column spaces, Scalar (mathematics), Self-adjoint operator, Semisimple algebra, Singular-value decomposition, Spectrum (functional analysis), Unit vector, Vector space, Von Neumann algebra. Expand index (16 more) » « Shrink index
Aequationes Mathematicae is a mathematical journal.
In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.
In mathematics, more specifically in functional analysis, a Banach space (pronounced) is a complete normed vector space.
In functional analysis, a bounded linear operator is a linear transformation L between normed vector spaces X and Y for which the ratio of the norm of L(v) to that of v is bounded above by the same number, over all non-zero vectors v in X. In other words, there exists some M\ge 0 such that for all v in X The smallest such M is called the operator norm \|L\|_ \, of L. A bounded linear operator is generally not a bounded function; the latter would require that the norm of L(v) be bounded for all v, which is not possible unless L(v).
In mathematics, the Cauchy–Schwarz inequality, also known as the Cauchy–Bunyakovsky–Schwarz inequality, is a useful inequality encountered in many different settings, such as linear algebra, analysis, probability theory, vector algebra and other areas.
In mathematics and multivariate statistics, the centering matrix is a symmetric and idempotent matrix, which when multiplied with a vector has the same effect as subtracting the mean of the components of the vector from every component.
In linear algebra, the characteristic polynomial of a square matrix is a polynomial which is invariant under matrix similarity and has the eigenvalues as roots.
In mathematics, the closed graph theorem is a basic result which characterizes continuous functions in terms of their graphs.
In mathematical analysis, a metric space M is called complete (or a Cauchy space) if every Cauchy sequence of points in M has a limit that is also in M or, alternatively, if every Cauchy sequence in M converges in M. Intuitively, a space is complete if there are no "points missing" from it (inside or at the boundary).
In mathematics, the conjugate transpose or Hermitian transpose of an m-by-n matrix A with complex entries is the n-by-m matrix A∗ obtained from A by taking the transpose and then taking the complex conjugate of each entry.
In linear algebra, a square matrix A is called diagonalizable if it is similar to a diagonal matrix, i.e., if there exists an invertible matrix P such that P−1AP is a diagonal matrix.
In abstract algebra, the direct sum is a construction which combines several modules into a new, larger module.
In mathematics, the dot product or scalar productThe term scalar product is often also used more generally to mean a symmetric bilinear form, for example for a pseudo-Euclidean space.
Dykstra's algorithm is a method that computes a point in the intersection of convex sets, and is a variant of the alternating projection method (also called the projections onto convex sets method).
In numerical analysis, one of the most important problems is designing efficient and stable algorithms for finding the eigenvalues of a matrix.
In linear algebra, an eigenvector or characteristic vector of a linear transformation is a non-zero vector that changes by only a scalar factor when that linear transformation is applied to it.
In linear algebra, a frame of an inner product space is a generalization of a basis of a vector space to sets that may be linearly dependent.
Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of vector spaces endowed with some kind of limit-related structure (e.g. inner product, norm, topology, etc.) and the linear functions defined on these spaces and respecting these structures in a suitable sense.
Geometry (from the γεωμετρία; geo- "earth", -metron "measurement") is a branch of mathematics concerned with questions of shape, size, relative position of figures, and the properties of space.
In mathematics, particularly linear algebra and numerical analysis, the Gram–Schmidt process is a method for orthonormalising a set of vectors in an inner product space, most commonly the Euclidean space Rn equipped with the standard inner product.
Graphical projection is a protocol, used in technical drawing, by which an image of a three-dimensional object is projected onto a planar surface without the aid of numerical calculation.
In mathematics, the Hahn–Banach theorem is a central tool in functional analysis.
In linear algebra, a Hessenberg matrix is a special kind of square matrix, one that is "almost" triangular.
The mathematical concept of a Hilbert space, named after David Hilbert, generalizes the notion of Euclidean space.
In linear algebra, a Householder transformation (also known as a Householder reflection or elementary reflector) is a linear transformation that describes a reflection about a plane or hyperplane containing the origin.
Idempotence is the property of certain operations in mathematics and computer science that they can be applied multiple times without changing the result beyond the initial application.
In mathematics, the infimum (abbreviated inf; plural infima) of a subset S of a partially ordered set T is the greatest element in T that is less than or equal to all elements of S, if such an element exists.
In linear algebra, an inner product space is a vector space with an additional structure called an inner product.
In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment.
In mathematics, an invariant subspace of a linear mapping T: V → V from some vector space V to itself is a subspace W of V that is preserved by T; that is, T(W) ⊆ W.
In mathematics, and more specifically in linear algebra and functional analysis, the kernel (also known as null space or nullspace) of a linear map between two vector spaces V and W, is the set of all elements v of V for which, where 0 denotes the zero vector in W. That is, in set-builder notation,.
A lattice is an abstract structure studied in the mathematical subdisciplines of order theory and abstract algebra.
Linear algebra is the branch of mathematics concerning linear equations such as linear functions such as and their representations through matrices and vector spaces.
In mathematics, a linear map (also called a linear mapping, linear transformation or, in some contexts, linear function) is a mapping between two modules (including vector spaces) that preserves (in the sense defined below) the operations of addition and scalar multiplication.
In statistics, linear regression is a linear approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables).
In linear algebra and related fields of mathematics, a linear subspace, also known as a vector subspace, or, in the older literature, a linear manifold, is a vector space that is a subset of some other (higher-dimension) vector space.
In mathematics, a matrix (plural: matrices) is a rectangular array of numbers, symbols, or expressions, arranged in rows and columns.
In mathematics, matrix multiplication or matrix product is a binary operation that produces a matrix from two matrices with entries in a field, or, more generally, in a ring or even a semiring.
In mathematical analysis, the maxima and minima (the respective plurals of maximum and minimum) of a function, known collectively as extrema (the plural of extremum), are the largest and smallest value of the function, either within a given range (the local or relative extrema) or on the entire domain of a function (the global or absolute extrema).
In linear algebra, the minimal polynomial of an matrix over a field is the monic polynomial over of least degree such that.
In mathematics, and in particular linear algebra, a pseudoinverse of a matrix is a generalization of the inverse matrix.
In mathematics, a normed vector space is a vector space over the real or complex numbers, on which a norm is defined.
Oblique projection is a simple type of technical drawing of graphical projection used for producing two-dimensional images of three-dimensional objects.
In functional analysis, an operator algebra is an algebra of continuous linear operators on a topological vector space with the multiplication given by the composition of mappings.
In mathematics, operator K-theory is a noncommutative analogue of topological K-theory for Banach algebras with most applications used for C*-algebras.
In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model.
In the mathematical fields of linear algebra and functional analysis, the orthogonal complement of a subspace W of a vector space V equipped with a bilinear form B is the set W⊥ of all vectors in V that are orthogonal to every vector in W. Informally, it is called the perp, short for perpendicular complement.
In mathematics, orthogonality is the generalization of the notion of perpendicularity to the linear algebra of bilinear forms.
In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace.
In mathematics, particularly linear algebra, an orthonormal basis for an inner product space V with finite dimension is a basis for V whose vectors are orthonormal, that is, they are all unit vectors and orthogonal to each other.
In linear algebra, an outer product is the tensor product of two coordinate vectors, a special case of the Kronecker product of matrices.
In functional analysis a partial isometry is a linear map between Hilbert spaces such that it is an isometry on the orthogonal complement of its kernel.
Pavel Grinfeld (also known as Greenfield) is an applied mathematician.
In modern mathematics, a point refers usually to an element of some set called a space.
In linear algebra, a QR decomposition (also called a QR factorization) of a matrix is a decomposition of a matrix A into a product A.
Riemannian geometry is the branch of differential geometry that studies Riemannian manifolds, smooth manifolds with a Riemannian metric, i.e. with an inner product on the tangent space at each point that varies smoothly from point to point.
In differential geometry, a branch of mathematics, a Riemannian submersion is a submersion from one Riemannian manifold to another that respects the metrics, meaning that it is an orthogonal projection on tangent spaces.
In linear algebra, the column space (also called the range or '''image''') of a matrix A is the span (set of all possible linear combinations) of its column vectors.
A scalar is an element of a field which is used to define a vector space.
In mathematics, a self-adjoint operator on a finite-dimensional complex vector space V with inner product \langle\cdot,\cdot\rangle is a linear map A (from V to itself) that is its own adjoint: \langle Av,w\rangle.
In ring theory, a branch of mathematics, a semisimple algebra is an associative artinian algebra over a field which has trivial Jacobson radical (only the zero element of the algebra is in the Jacobson radical).
In linear algebra, the singular-value decomposition (SVD) is a factorization of a real or complex matrix.
In mathematics, particularly in functional analysis, the spectrum of a bounded operator is a generalisation of the set of eigenvalues of a matrix.
In mathematics, a unit vector in a normed vector space is a vector (often a spatial vector) of length 1.
A vector space (also called a linear space) is a collection of objects called vectors, which may be added together and multiplied ("scaled") by numbers, called scalars.
In mathematics, a von Neumann algebra or W*-algebra is a *-algebra of bounded operators on a Hilbert space that is closed in the weak operator topology and contains the identity operator.
Linear projection, Orthogonal projection, Orthogonal projection operator, Orthogonal projections, Orthogonal projector, Projection operator, Projection operators, Projector (linear algebra), Projector operator.