In linear algebra, a convergent matrix is a matrix that converges to the zero matrix under matrix exponentiation.


When successive powers of a matrix T become small (that is, when all of the entries of T approach zero, upon raising T to successive powers), the matrix T converges to the zero matrix. A regular splitting of a non-singular matrix A results in a convergent matrix T. A semi-convergent splitting of a matrix A results in a semi-convergent matrix T. A general iterative method converges for every initial vector if T is convergent, and under certain conditions if T is semi-convergent.


We call an n × n matrix T a convergent matrix if






for each i = 1, 2, ..., n and j = 1, 2, ..., n.[1][2][3]



Computing successive powers of T, we obtain

and, in general,



T is a convergent matrix. Note that ρ(T) = 1/4, where ρ(T) represents the spectral radius of T, since 1/4 is the only eigenvalue of T.


Let T be an n × n matrix. The following properties are equivalent to T being a convergent matrix:

  1. for some natural norm;
  2. for all natural norms;
  3. ;
  4. for every x.[4][5][6][7]

Iterative methods

Main article: Iterative method

A general iterative method involves a process that converts the system of linear equations






into an equivalent system of the form






for some matrix T and vector c. After the initial vector x(0) is selected, the sequence of approximate solution vectors is generated by computing






for each k ≥ 0.[8][9] For any initial vector x(0), the sequence defined by (4), for each k ≥ 0 and c ≠ 0, converges to the unique solution of (3) if and only if ρ(T) < 1, that is, T is a convergent matrix.[10][11]

Regular splitting

Main article: Matrix splitting

A matrix splitting is an expression which represents a given matrix as a sum or difference of matrices. In the system of linear equations (2) above, with A non-singular, the matrix A can be split, that is, written as a difference






so that (2) can be re-written as (4) above. The expression (5) is a regular splitting of A if and only if B−10 and C0, that is, B−1 and C have only nonnegative entries. If the splitting (5) is a regular splitting of the matrix A and A−10, then ρ(T) < 1 and T is a convergent matrix. Hence the method (4) converges.[12][13]

Semi-convergent matrix

We call an n × n matrix T a semi-convergent matrix if the limit






exists.[14] If A is possibly singular but (2) is consistent, that is, b is in the range of A, then the sequence defined by (4) converges to a solution to (2) for every x(0) if and only if T is semi-convergent. In this case, the splitting (5) is called a semi-convergent splitting of A.[15]

See also


  1. ^ Burden & Faires (1993, p. 404)
  2. ^ Isaacson & Keller (1994, p. 14)
  3. ^ Varga (1962, p. 13)
  4. ^ Burden & Faires (1993, p. 404)
  5. ^ Isaacson & Keller (1994, pp. 14, 63)
  6. ^ Varga (1960, p. 122)
  7. ^ Varga (1962, p. 13)
  8. ^ Burden & Faires (1993, p. 406)
  9. ^ Varga (1962, p. 61)
  10. ^ Burden & Faires (1993, p. 412)
  11. ^ Isaacson & Keller (1994, pp. 62–63)
  12. ^ Varga (1960, pp. 122–123)
  13. ^ Varga (1962, p. 89)
  14. ^ Meyer & Plemmons (1977, p. 699)
  15. ^ Meyer & Plemmons (1977, p. 700)