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  • Linear transformations

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  • Eigenvalues and eigenvectors
  • Terminology
  • Geometric properties of linear transformations
  • Matrices as linear transformations
  • Basic properties of linear transformations
  • Description of a spanning set for the null space of a matrix from the reduced row-echelon form.
  • Description of a basis for the null space of a matrix from the reduced row-echelon form.
  • The nonzero rows of an echelon form of a matrix are linearly independent.
  • Subspaces associated to a matrix
  • Rank and nullity
  • Examples
  • Composition
  • The preimage of a vector is a translation of the kernel of the linear transformation
  • The image of a linearly independent set under an injective linear transformation is linearly independent.
  • The dimension of the domain of an injective linear transformation is at most the dimension of the codomain.
  • The dimension of the domain of a surjective linear transformation is at least the dimension of the codomain.
  • A linear transformation is surjective if and only if the rank equals the dimension of the codomain.
  • The range of a linear transformation is a subspace
  • The the image of a spanning set is a spanning set for the range space
  • A linear transformation is surjective if and only if the image of a basis is a spanning set
  • Definition of generalized range space of a linear transformation
  • A linear transformation is injective on its generalized range space.
  • Definition of diagonalizable linear transformation
  • A linear transformation is diagonalizable if there is a basis such that each element is an eigenvector of the transformation.
  • Subspaces associated to a linear transformation
  • The rank plus the nullity of a linear transformation equals the dimension of the domain.
  • The image of a linearly dependent set under a linear transformation is linearly dependent.
  • A linear transformation is onto if and only if its rank equals the number of rows in any matrix representation.
  • A linear transformation is invertible if and only if it is injective and surjective
  • Definition of matrix representation of a linear transformation with respect to bases of the spaces
  • A linear transformation is given by multiplying by its matrix representation with respect to bases of the spaces
  • Definition of matrix representation of a linear transformation from a vector space to itself
  • The matrix representation of a scalar multiple of linear transformations is the scalar multiple of the matrix.
  • The matrix representation of a sum of linear transformations is the sum of the matrices.
  • The matrix representation of a composition of linear transformations is the product of the matrices.
  • The matrix representation of the inverse of linear transformations is the inverse of the matricix.
  • A linear transformation has the same eigenvalues and eigenvectors as any matrix representation.
  • A linear transformation has a representation as an upper triangular matrix.
  • Equivalence theorems for injective transformations
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  1. A linear transformation is diagonalizable if there is a basis such that each element is an eigenvector of the transformation.

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  • Definition of matrix-scalar multiplication#23471
  • Definition of matrix-vector product#23483
  • Definition of m by n matrix#23452
  • Definition of minimal polynomial of a linear transformation#24045
  • Definition of minimal polynomial of a matrix#23703
  • Definition of multilinear function#23733
  • Definition of nilpotent linear transformation#23860
  • Definition of nilpotent matrix#23581
  • Definition of nonsingular matrix: matrix is invertible#23641
  • Definition of nonsingular matrix: the associated homogeneous linear system has only the trivial solution#23642
  • Definition of nontrivial solution to a homogeneous linear system of equations#23435
  • Definition of normal matrix#23600
  • Definition of norm/length of a vector#23908
  • Definition of (not necessarily orthogonal) projection onto a component of a direct sum#23940
  • Definition of nullity of a linear transformation#23884
  • Definition of nullity of a matrix#23675
  • Definition of one-to-one/injective linear transformation#23845
  • Definition of onto/surjective linear transformation#23844
  • Definition of orthogonal basis of a (sub)space#23928
  • Definition of orthogonal complement of a subspace#23920
  • Definition of orthogonally diagonalizable matrix#23577
  • Definition of orthogonal matrix#23586
  • Definition of (orthogonal) projection of one vector onto another vector#23938
  • Definition of (orthogonal) projection onto a subspace#23941
  • Definition of orthogonal set of vectors#23925
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