Explore Eigenvector on MathWorld

An eigenvector is one of a special set of vectors associated with a linear system of equations.

Eigenvector is a college-level concept that would be first encountered in a linear algebra course.


Linear Transformation: A function from one vector space to another. If bases are chosen for the vector spaces, a linear transformation can be given by a matrix.
Matrix: A matrix is a concise and useful way of uniquely representing and working with linear transformations. In particular, for every linear transformation, there exists exactly one corresponding matrix, and every matrix corresponds to a unique linear transformation. The matrix is an extremely important concept in linear algebra.
Vector Space: A vector space is a set that is closed under finite vector addition and scalar multiplication. The basic example is n-dimensional Euclidean space.

Classroom Articles on Linear Algebra (Up to College Level)

  • Eigenvalue
  • Matrix Inverse
  • Euclidean Space
  • Matrix Multiplication
  • Inner Product
  • Norm
  • Linear Algebra