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  • Linear systems have 0
  • Linear systems of equations
  • Linear transformations
  • LU decomposition
  • Matrices
  • Matrices act as a transformation by multiplying vectors
  • Matrices as linear transformations
  • Matrix addition is commutative and associative.
  • Matrix adjoint is an involution.
  • Matrix conjugation is an involution.
  • Matrix describing a rotation of the plane
  • Matrix diagonalization
  • Matrix equations
  • Matrix equivalence
  • Matrix inverse is an involution.
  • Matrix inverses are unique: if A and B are square matrices
  • Matrix multiplication can be viewed as the dot product of a row vector of column vectors with a column vector of row vectors
  • Matrix multiplication is associative.
  • Matrix multiplication is distributive over matrix addition.
  • Matrix multiplication is not commutative in general.
  • Matrix representation of a composition of linear transformations is given by a matrix product
  • Matrix-scalar multiplication is commutative
  • Matrix-scalar product is commutative
  • Matrix transpose commutes with matrix inverse.
  • Matrix transpose is an involution.
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