Difference between revisions of "Linear algebra"

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*Subspaces
 
*Subspaces
 
:*[[image]] and [[kernel]]
 
:*[[image]] and [[kernel]]
−
:*[[basis]]
+
:*[[basis]] and [[span]]
 
:*[[dimension]]
 
:*[[dimension]]
  
 
*[[Determinant]]s
 
*[[Determinant]]s
 +
:*geometrical interpretation
 +
:*Cramer's rule
  
 
*[[Basis]]
 
*[[Basis]]
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*[[Eigenvalue]]s and [[eigenvector]]s
 
*[[Eigenvalue]]s and [[eigenvector]]s
 +
:*diagonalization
 +
:*complex eigenvalues
  
 
*[[Orthogonality]]
 
*[[Orthogonality]]

Revision as of 03:54, April 28, 2010

Linear algebra is the mathematical subject that studies vectors, vector spaces, linear maps, and systems of linear equations. Branches of Linear algebra typically include Linear equations, Matrices, Matrix decompositions, Computations, Vectors, Vector spaces, Multilinear algebra, Affine space, Projective space.[1] Linear algebra has numerous applications in engineering, chemistry and physics.

Basic Concepts

  • coefficient matrices and Gauss-Jordan elimination
  • geometric representations, especially vectors
  • transformations, inverses and matrix products
  • Subspaces
  • geometrical interpretation
  • Cramer's rule
  • diagonalization
  • complex eigenvalues
  • Symmetric matrix
  • Quadratic forms
  • Linear dynamical systems
  • Euler's Formula

More advanced topics include

  • the conditions of a vector space
  • isomorphisms
  • Nth dimensional spaces and subspaces
  • Inner spaces
  • inner product spaces
  • Stability
  • Hermitian Matrices
  • Linear differential equations

Common problems

Common problems in linear algebra include:

References