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  • Operations on matrices

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  • Addition
  • Conjugation
  • Scalar multiplication
  • Row operations
  • Matrix-vector products
  • Multiplication
  • Transpose and adjoint
  • Inverse

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  • Definition of left inverse of a matrix
  • Definition of right inverse of a matrix
  • Definition of inverse of a matrix
  • Definition of invertible matrix
  • If a matrix has both a left and a right inverse
  • If a square matrix has a one-sided inverse
  • Formula for the inverse of a 2-by-2 matrix.
  • Matrix inverse is an involution.
  • For n-by-n invertible matrices A and B
  • The product of square matrices is nonsingular if and only if each factor is nonsingular.
  • The inverse of a scalar multiple is the reciprocal times the inverse.
  • Matrix transpose commutes with matrix inverse.
  • The inverse of a matrix (if it exists) can be found by row reducing the matrix augmented by the identity matrix.
  • Example of finding the inverse of a 2-by-2 matrix by row reducing the augmented matrix
  • Example of finding the inverse of a 2-by-2 matrix by using a formula
  • Example of finding the inverse of a 3-by-3 matrix by row reducing the augmented matrix
  • Example of finding the inverse of a 3-by-3 matrix by using Cramer's rule
  • The inverse of a matrix can be used to solve a linear system.
  • Matrix inverses are unique: if A and B are square matrices
  • Definition of generalized inverse of a matrix
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  • Proof of several equivalences for nonsingular matrix#23644
  • QR decomposition#23630
  • Rank and mullity#23672
  • Rank and nullity#23882
  • Removing a linearly dependent vector from a set does not change the span of the set.#23982
  • R^n is a vector space.#24097
  • Row equivalence is an equivalence relation#23480
  • Row equivalent matrices have the same row space.#23881
  • Row equivalent matrices represent equivalent linear systems#23769
  • Row operations#23474
  • Row operations are given by multiplication by elementary matrices.#23559
  • Row operations do not necessarily preserve the column space.#23878
  • Scalar multiplication#23470
  • Similarity of matrices#23634
  • Similarity of matrices in an equivalence relation.#23636
  • Similar matrices have the same eigenvalues and the same characteristic polynomials.#23638
  • Spans#23804
  • Subspaces#23811
  • Subspaces associated to a linear transformation#24055
  • Subspaces associated to a matrix#23872
  • Switching two rows multiplies the determinant by -1.#23738
  • Symmetric matrices#23571
  • Symmetric matrices are square.#23573
  • Terminology#23754
  • The 0 scalar multiplied by any vector equals the 0 vector.#23960
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  • Aspen Summer 2016 - Entanglement Matters#1213
  • Math#23168

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