Advances in Pure Mathematics
Vol.2 No.5(2012), Article ID:22805,5 pages DOI:10.4236/apm.2012.25050
On the Infinite Products of Matrices
1National Research Institute of Astronomy and Geophysics, Helwan, Egypt
2Faculty of Science, Helwan University, Helwan, Egypt
Email: yousry_hanna@yahoo.com
Received May 29, 2012; revised June 27, 2012; accepted July 5, 2012
Keywords: matrices; infinite products; iteration
ABSTRACT
In different fields in space researches, Scientists are in need to deal with the product of matrices. In this paper, we develop conditions under which a product of matrices chosen from a possibly infinite set of matrices
converges. There exists a vector norm such that all matrices in M are no expansive with respect to this norm and also a subsequence
of the sequence of nonnegative integers such that the corresponding sequence of operators
converges to an operator which is paracontracting with respect to this norm. The continuity of the limit of the product of matrices as a function of the sequences
is deduced. The results are applied to the convergence of inner-outer iteration schemes for solving singular consistent linear systems of equations, where the outer splitting is regular and the inner splitting is weak regular.
1. Introduction
Let the standard iterative method for solving the system of linear equations
(1)
where and x, b are n-vectors [1], be induced by the splitting of A into
, where T is a nonsingular matrix. Starting with an arbitrary vector
, the recurrence relation
(2)
is used to compute a sequence of iterations whose limit should be the solution to equation (1).
If A is a nonsingular matrix, to obtain a good approximation to the solution of Equation (1), one need not to even solve the system (2) exactly for each. For each
, we solve the system (2) by iterations. Then split the matrix T into
(3)
where the matrix G is invertible. Then, starting with inner iterations
(4)
are computed after which one resets. The entire inner-outer iteration process can then be expressed as follows [2-4]
(5)
where
(6)
If the spectral radius of both and
are smaller than 1 so that the powers of both iteration matrices converge to zero, then for sufficiently large positive integer t we have that if
[5], the sequence
produced by the inner-outer iterations converges to the solution of equation (1) from all initial vectors zo. If A and T have a nonnegative inverse and both iteration matrices
and
are nonnegative matrices, with the former induced by a regular splitting of A and the latter induced by a weak regular splitting of T, then the sequence
converges to the solution of Equation (1) whenever
with no restrictions on t [4]. The process of inner-outer iterations can be represented by means of an iteration matrix at every stage, the spectral radius of such a matrix can no longer be less than 1. Furthermore, even if the spectral radius of the iteration matrix at each stage is 1, this does not ensure the convergence of the inner-outer iteration process even if a fixed number of iterations are used between every two outer iterations [6]. If the number of inner iterations, between every two outer iterations, is allowed to vary, the problem is further compounded [7,8]. Here we shall examine some connections between the work here and problems of convergence of infinite products of matrices such as considered by [6].
If one is going to employ the inner-outer iteration scheme, then it is very reasonable that often between any two outer iterations only a relatively small number of inner iterations will be computed and only in rare cases much more inner iteration will be allowed. This effectively means that there is a number, such that infinitely often at most n inner iterations will be carried out between any two outer ones. This implies that there exists an index
such that for an infinite subsequence ik of the positive integers,
, infinitely often,
. We shall prove that under certain convergence properties of
such as
is paracontracting with respect to a vector norm in respect of which all the
are no expansive, the inner-outer iteration (5) for any initial vector zo. This implies that the inner-outer iteration scheme is convergent when the system (1) is consistent.
Now let we have an infinite set of matrices
, and there exists a vector norm
on Cn such that each matrix in M is no expansive with respect to
. From M select an infinite sequence of matrices
. Then if
contains a subsequence
which converges to a matrix H which is paracontracting with respect to
and such that the null space
is contained in the intersection of the null spaces
, then
. Finally, let D be the set of all sequences
of integers such that each sequence
contains an integer
such that
for infinitely many
. Then, according to Th. 3.1 if corresponding to the sequence
, the matrix
is paracontracting, then
We shall show that the function is continuous.
2. Preliminaries
Let. We shall denote both of the null space and the range of E by
and
respectively. Recall that the Jordan blocks of E corresponding to 0 are 1 × 1 if and only if
and
a situation which we shall write as
.
Recall further that according to [9] the powers of a matrix converges if and only if
and
where denotes the spectrum of a matrix.
For a vector we shall write that
if all the entries of x are positive numbers. Also, let
enote a vector norm in. An n × n matrix E is no expansive with respect to
if for all
,
E is called paracontracting with respect to if for all
We denote by the set of all matrices in
which are paracontracting with respect to
. Two examples of paracontracting matrices are as follows. For the Euclidian norm it is known that any Hermitian matrix whose eigenvalues lie in (−1, 1] is paracontracting. Suppose now that E is an n × n positive matrix whose spectral radius is 1 and with a Perron vector
. We claim that such a matrix is paracontracting with respect to
, the monotonic vector norm induced by x. Let
be any vector satisfying
or, equivalently, not being a multiple of x. We know that
By the positively of E and because, it follows that for any
such that
, so that
.
The concept of paracontraction was introduced by [4] who showed that the product of any number of matrices in is again an element of
. Moreover, they used a result of [3] to show that the powers of any matrix
converge. Thus, in particular such matrix has the property that
.
Finally, recall that a splitting of A into A = T – Q is called regular if T is nonsingular, and
. Regular splitting where introduced by [10], who showed that for a regular splitting,
if and only if A is nonsingular and
. A splitting A = T – Q is called weak regular if T is nonsingular,
and
. This concept was introduced by [11] who showed that, even allowing for this weakening of the assumption on regular splitting,
if and only if A is nonsingular and
. If A = T – Q is a regular splitting of A, then
and
if and only if A is range monotone [12], that is,
.
Moreover, they showed that if there exists a vector such that
, then
and
, and such a positive vector always exists if A is a singular and irreducible M-matrix.
3. Applications to Singular Systems
As we mentioned before, if is a regular splitting for
and
is range monotone, then
and
.
Now, let is a weak regular splitting for
and consider the inner-outer iteration process
(7)
where
(8)
We observe at once that since is a regular splitting for
and
is a weak regular splitting for
, any of the inner-outer iteration operators
, is a nonnegative matrix. Already Nichols in [3] essentially showed the following relation holds:
(9)
Suppose that the n x n coefficient matrix A (assumed to be nonsingular) in the system (1) is monotone. For each, let
be a regular splitting of
and
be a weak regular splitting. Consider the inner-outer iteration process:
where as, in the introduction, and
If there are splitting and
such that for infinitely many is
and
simultaneously, then for any
,
Now, suppose is a range monotone and that
and
are regular and weak regular splitting for A and T respectively, then
and
for all [2,10,13].
Once again, suppose that and
are regular and weak regular splitting for A and T respectively. Note that the range monotone of A was used only to deduce that
is an M-matrix of index at most 1. Another condition which ensures that
is an M-matrix of index at most 1 is that there exists a positive vector x such that
for then
. Furthermore, such a vector exists when A is a singular and irreducible M-matrix. When A is such an M-matrix, then, in fact, there exists a positive vector x such that
. But then also
so that, and hence
We can thus conclude that when A is an irreducible M-matrix, not only the conclusions of the above result hold, but so that
. Hence for each
is no expansive with respect to the norm
. We also see that
Now we know that. Thus if either
or
, then it follows that
so that inductively,
Let. Then from the relation
we see that, not only
, (10)
a fact that already follows from, but that the rate of convergence behaves as
.
Theorem: Let be a set of matrices in
, let
be a sequence of matrices chosen from M, and consider the iteration scheme
Suppose that all are no expansive with respect to the same vector norm
and there exists a subsequence
of the sequence
such that
where V is a matrix with the following properties:
• V is paracontracting with respect to.
Then for any the sequence
is convergent and
.
The proof is given in [2].
From the above analysis and previous theorem we can now state the following result concerning the convergence of the inner-outer iteration process:
Theorem: Let and suppose that
and
are a regular splitting and a weak regular splitting for A and T, respectively, and consider the inner-outer iteration process (7) for solving the consistent linear system Ax = b. Suppose there exists a vector
such that
and one of the following conditions is satisfied:
1) For some integer j, is paracontracting and for infinitely many integers k,
.
2) is paracontracting with respect to
, the sequence
is unbounded, and either
or
.
The sequence of iterations generated by the scheme given in (7) converges to a solution of the system Ax = b.
Proof. We have the identity that
from which it follows that x is a positive vector for which
showing that for each is no expansive with respect to the monotonic vector norm induced by x. Also the proof of (2) is clear because the unboundness of the sequence
together with the existence of the limit in Equation (10) now means that the sequence of matrices
contains an infinite subsequence of matrices which converges to the paracontracting matrix V.
4. Conclusion
The conditions under which the product of matrices converges are explained and we apply the results for the convergence of inner-outer iteration schemes for solving singular consistent linear system of equations.
REFERENCES
- Y. S. Hanna, “On the Solutions of Tridiagonal Linear System,” Applied Mathematics and Computation, Vol. 189, 2007, pp. 2011-2016.
- R. Bru, L. Elsner and M. Neumann, “Convergence of Infinite Products of Matrices and Inner-Outer Iteration Schemes,” Electronic Transactions on Numerical Analysis, Vol. 2, 1994, pp. 183-193.
- N. K. Nichols, “On the Convergence of Two-Stage Iterative Processes for Solving Linear Equations,” SIAM Journal on Numerical Analysis, Vol. 10, No. 3, 1973, pp. 460-469. doi:10.1137/0710040
- P. J. Lanzkron, D. J. Rose and D. B. Szyld, “Convergence of Nested Classical Iterative Methods for Linear Systems,” Numerische Mathematik, Vol. 58, 1991, pp. 658- 702.
- A. Frommer and D. B. Szyld, “H-Splittings and TwoStage Iterative Methods,” Numerische Mathematik, Vol. 63, No. 1, 1992, pp. 345-356. doi:10.1007/BF01385865
- I. Daubechifs and J. C. Lagarias, “Sets of Matrices All Infinite Products of Which Converge,” Linear Algebra and Its Applications, Vol. 161, 1992, pp. 227-263. doi:10.1016/0024-3795(92)90012-Y
- R. Bru, L. Elsner and M. Neumann, “Models of Parallel Chaotic Iteration Methods,” Linear Algebra and Its Applications, Vol. 102, 1988, pp. 175-192. doi:10.1016/0024-3795(88)90227-3
- L. Elsner, I. Koltracht and M. Neumann, “On the Convergence of Asynchronous Paracontractions with Application to Tomographic Reconstruction from Incomplete Data,” Linear Algebra and Its Applications, Vol. 130, 1990, pp. 65-82. doi:10.1016/0024-3795(90)90206-R
- S. Nelson and M. Neumann, “Generalizations of the Projection Method with Applications to SOR Theory for Hermitian Positive Semidefinite Linear Systems,” Numerische Mathematik, Vol. 51, No. 2, 1987, pp. 123-141. doi:10.1007/BF01396746
- R. S. Varga, “Matrix Iterative Analysis,” Prentice-Hall, Englewood Cliffs, 1961.
- J. M. Optega and W. Rueinboldt, “Monotone Iterations for Nonlinear Equations with Application to Gauss-Seidel Methods,” SIAM Journal on Numerical Analysis, Vol. 4, No. 2, 1967, pp. 171-190. doi:10.1137/0704017
- M. Neumann and R. J. Plemmons, “Convergent Nonnegative Matrices and Iterative Methods for Consistent Linear Systems,” Numerische Mathematik, Vol. 31, No. 3, 1978, pp. 265-279. doi:10.1007/BF01397879
- M. Neumann and R. J. Plemmons, “Generalized Inverse-Positivity and Splittings of M-Matrices,” Linear Algebra and Its Applications, Vol. 23, 1979, pp. 21-35. doi:10.1016/0024-3795(79)90090-9