Faster access than browser!Similarities between Eigenvalues and eigenvectors and Transpose
Eigenvalues and eigenvectors and Transpose have 22 things in common (in Unionpedia): Arthur Cayley, Basis (linear algebra), Characteristic polynomial, Complex conjugate, Complex number, Conjugate transpose, Determinant, Dot product, Hermitian matrix, Invertible matrix, Linear algebra, Linear map, Matrix (mathematics), Module (mathematics), Orthogonal matrix, Positive-definite matrix, Scalar (mathematics), Skew-symmetric matrix, Square matrix, Symmetric matrix, Unitary matrix, Vector space.
Arthur Cayley
Arthur Cayley F.R.S. (16 August 1821 – 26 January 1895) was a British mathematician.
Arthur Cayley and Eigenvalues and eigenvectors · Arthur Cayley and Transpose ·
Basis (linear algebra)
In mathematics, a set of elements (vectors) in a vector space V is called a basis, or a set of, if the vectors are linearly independent and every vector in the vector space is a linear combination of this set.
Basis (linear algebra) and Eigenvalues and eigenvectors · Basis (linear algebra) and Transpose ·
Characteristic polynomial
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.
Characteristic polynomial and Eigenvalues and eigenvectors · Characteristic polynomial and Transpose ·
Complex conjugate
In mathematics, the complex conjugate of a complex number is the number with an equal real part and an imaginary part equal in magnitude but opposite in sign.
Complex conjugate and Eigenvalues and eigenvectors · Complex conjugate and Transpose ·
Complex number
A complex number is a number that can be expressed in the form, where and are real numbers, and is a solution of the equation.
Complex number and Eigenvalues and eigenvectors · Complex number and Transpose ·
Conjugate transpose
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.
Conjugate transpose and Eigenvalues and eigenvectors · Conjugate transpose and Transpose ·
Determinant
In linear algebra, the determinant is a value that can be computed from the elements of a square matrix.
Determinant and Eigenvalues and eigenvectors · Determinant and Transpose ·
Dot product
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.
Dot product and Eigenvalues and eigenvectors · Dot product and Transpose ·
Hermitian matrix
In mathematics, a Hermitian matrix (or self-adjoint matrix) is a complex square matrix that is equal to its own conjugate transpose—that is, the element in the -th row and -th column is equal to the complex conjugate of the element in the -th row and -th column, for all indices and: Hermitian matrices can be understood as the complex extension of real symmetric matrices.
Eigenvalues and eigenvectors and Hermitian matrix · Hermitian matrix and Transpose ·
Invertible matrix
In linear algebra, an n-by-n square matrix A is called invertible (also nonsingular or nondegenerate) if there exists an n-by-n square matrix B such that where In denotes the n-by-n identity matrix and the multiplication used is ordinary matrix multiplication.
Eigenvalues and eigenvectors and Invertible matrix · Invertible matrix and Transpose ·
Linear 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.
Eigenvalues and eigenvectors and Linear algebra · Linear algebra and Transpose ·
Linear map
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.
Eigenvalues and eigenvectors and Linear map · Linear map and Transpose ·
Matrix (mathematics)
In mathematics, a matrix (plural: matrices) is a rectangular array of numbers, symbols, or expressions, arranged in rows and columns.
Eigenvalues and eigenvectors and Matrix (mathematics) · Matrix (mathematics) and Transpose ·
Module (mathematics)
In mathematics, a module is one of the fundamental algebraic structures used in abstract algebra.
Eigenvalues and eigenvectors and Module (mathematics) · Module (mathematics) and Transpose ·
Orthogonal matrix
In linear algebra, an orthogonal matrix is a square matrix whose columns and rows are orthogonal unit vectors (i.e., orthonormal vectors), i.e. where I is the identity matrix.
Eigenvalues and eigenvectors and Orthogonal matrix · Orthogonal matrix and Transpose ·
Positive-definite matrix
In linear algebra, a symmetric real matrix M is said to be positive definite if the scalar z^Mz is strictly positive for every non-zero column vector z of n real numbers.
Eigenvalues and eigenvectors and Positive-definite matrix · Positive-definite matrix and Transpose ·
Scalar (mathematics)
A scalar is an element of a field which is used to define a vector space.
Eigenvalues and eigenvectors and Scalar (mathematics) · Scalar (mathematics) and Transpose ·
Skew-symmetric matrix
In mathematics, particularly in linear algebra, a skew-symmetric (or antisymmetric or antimetric) matrix is a square matrix whose transpose equals its negative; that is, it satisfies the condition In terms of the entries of the matrix, if aij denotes the entry in the and; i.e.,, then the skew-symmetric condition is For example, the following matrix is skew-symmetric: 0 & 2 & -1 \\ -2 & 0 & -4 \\ 1 & 4 & 0\end.
Eigenvalues and eigenvectors and Skew-symmetric matrix · Skew-symmetric matrix and Transpose ·
Square matrix
In mathematics, a square matrix is a matrix with the same number of rows and columns.
Eigenvalues and eigenvectors and Square matrix · Square matrix and Transpose ·
Symmetric matrix
In linear algebra, a symmetric matrix is a square matrix that is equal to its transpose.
Eigenvalues and eigenvectors and Symmetric matrix · Symmetric matrix and Transpose ·
Unitary matrix
In mathematics, a complex square matrix is unitary if its conjugate transpose is also its inverse—that is, if where is the identity matrix.
Eigenvalues and eigenvectors and Unitary matrix · Transpose and Unitary matrix ·
Vector space
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.
Eigenvalues and eigenvectors and Vector space · Transpose and Vector space ·
The list above answers the following questions
- What Eigenvalues and eigenvectors and Transpose have in common
- What are the similarities between Eigenvalues and eigenvectors and Transpose
Eigenvalues and eigenvectors and Transpose Comparison
Eigenvalues and eigenvectors has 235 relations, while Transpose has 50. As they have in common 22, the Jaccard index is 7.72% = 22 / (235 + 50).
References
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