Convergent matrix

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

Background

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.

Definition

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

 

 

 

 

(1)

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

Example

Let

Computing successive powers of T, we obtain

and, in general,

Since

and

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.

Characterizations

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

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

 

 

 

 

(2)

into an equivalent system of the form

 

 

 

 

(3)

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

 

 

 

 

(4)

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

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

 

 

 

 

(5)

so that (2) can be re-written as (4) above. The expression (5) is a regular splitting of A if and only if B1 0 and C 0, that is, B1 and C have only nonnegative entries. If the splitting (5) is a regular splitting of the matrix A and A1 0, 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

 

 

 

 

(6)

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

Notes

References

  • Burden, Richard L.; Faires, J. Douglas (1993), Numerical Analysis (5th ed.), Boston: Prindle, Weber and Schmidt, ISBN 0-534-93219-3.
  • Isaacson, Eugene; Keller, Herbert Bishop (1994), Analysis of Numerical Methods, New York: Dover, ISBN 0-486-68029-0.
  • Carl D. Meyer, Jr.; R. J. Plemmons (Sep 1977). "Convergent Powers of a Matrix with Applications to Iterative Methods for Singular Linear Systems". SIAM Journal on Numerical Analysis. 14 (4): 699–705. doi:10.1137/0714047.
  • Varga, Richard S. (1960). "Factorization and Normalized Iterative Methods". In Langer, Rudolph E. (ed.). Boundary Problems in Differential Equations. Madison: University of Wisconsin Press. pp. 121–142. LCCN 60-60003.
  • Varga, Richard S. (1962), Matrix Iterative Analysis, New Jersey: Prentice–Hall, LCCN 62-21277.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.