Advances in Linear Algebra & Matrix Theory
Vol.05 No.02(2015), Article ID:56990,8 pages
10.4236/alamt.2015.52004
Inverse Nonnegativity of Tridiagonal M-Matrices under Diagonal Element-Wise Perturbation
Mohamed A. Ramadan1, Mahmoud M. Abu Murad2
1Department of Mathematics, Faculty of Science, Menoufia University, Shebeen El-Kom, Egypt
2Department of Mathematics, Faculty of Science, Zagazig University, Ash Sharqiyah, Egypt
Email: ramadanmohamed13@yahoo.com, mramadan@eun.eg, abomorad1978@yahoo.com, mabumurad@su.edu.sa
Copyright © 2015 by authors and Scientific Research Publishing Inc.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/



Received 24 March 2015; accepted 6 June 2015; published 9 June 2015
ABSTRACT
One of the most important properties of M-matrices is element-wise non-negative of its inverse. In this paper, we consider element-wise perturbations of tridiagonal M-matrices and obtain bounds on the perturbations so that the non-negative inverse persists. The largest interval is given by which the diagonal entries of the inverse of tridiagonal M-matrices can be perturbed without losing the property of total nonnegativity. A numerical example is given to illustrate our findings.
Keywords:
Totally Positive Matrix, Totally Nonnegative Matrix, Tridiagonal Matrices, Compound Matrix, Element-Wise Perturbations

1. Introduction
In many mathematical problems,
-matrices and
-matrices play an important role. It is often useful to know the properties of their inverses, especially when the
-matrices and the M-matrices have a special combinatorial structure, for more details we refer the reader [1] . M-matrices have important applications, for instance, in iterative methods, in numerical analysis, in the analysis of dynamical systems, in economics, and in mathematical programming. One of the most important properties of some kinds of M-matrices is the nonegativity of their inverses, which plays central role in many of mathematical problems.
An
real matrix
is called M-matrix if
,
and
,
, over the years, M-matrices have considerable attention, in large part because they arise in many applications [2] [3] . Recently, a noticeable amount of attention has turned to the inverse of tridiagonal M-matrices (those matrices which happen to be inverses of special form of M-matrices with property
whenever
) and
is generalized strictly diagonally dominant. A matrix is said to be generalized (strictly) diagonally dominant
if
. Of particular importance to us is the fact that since
is an M-matrix it is non-singular and
>0where the inequality is satisfied element-wise. A rich class of M-matrices were introduced by Ostrowski in 1937 [4] , with reference to the work of Minkowski [5] [6] . A condition which is easy to check is that a matrix
is an M-matrix if and only if



In this paper, we consider the inverse of perturbed M-matrix. Specifically we consider the effect of changing single elements inside the diagonal of

The reminder of the paper is organized as follows. In section 2, we explain our notations and some needed important definitions are presented. In section 3, some auxiliary results and important prepositions and lemmas are stated. In section 4, we present our results.
2. Notations
In this section we introduce the notation that will be used in developing the paper. For 



















denoted by

Throughout this paper we use the following notation for general tridiagonal M-matrix:
where




We let 

Definition 2.1 Compound Matrices ([7] , p. 19).
Let 






Construct the following table which depends on
The created matrix
is called

For example, if




Then
3. Auxiliary Results
We start with some basic facts on tridiagonal M-matrices. We can find the determinant of any 

And we have the following proposition for finding the determinant of a 

Proposition 3.1 ([10] , formula 4.1) For any 


We will present now some of propositions of nonsingular totally nonnegative matrices which important for our work.
Proposition 3.2 [10] [11]
For any nonsingular totally nonnegative matrix
That is


Proposition 3.3 ([7] , p. 21)
Let M be a nonsingular tridiagonal M-matrix, and 

In the sequel we will make use the following lemma, see, e.g. [12] .
Lemma 3.4 (Sylvester Identity)
Partition square matrix 


where 





Define the submatrices
If 
Lemma 3.5 ([11] , p.199) Let 




We now state an important result which links the determinant of M-matrix with the value of the elements of its inverse.
Lemma 3.6 [10] Let 
verse matrix 

4. Main Results
In this section, we present our results based on the inverse of tridiagonal M-matrices. Firstly we begin with the following theorem.
Theorem 4.1
Let 
If 


tive matrix. Moreover, 
Proof: Let 
Then 

You can find this formula in ([7] , p. 21).
There is an explicit formula for the determinant of 
Multiply the first row by 

where
And now apply an induction argument to get the result.
Numerical Example: Let 


Note that 
Numerically we can conclude the following fact.
Fact: For any 


Moreover,
To prove this result we use Theorem 4.1.
Suppose M is nonsingular then
For example, when

Similarly we can find
Illustrative Example: Let 
Note that
Observe that the error came from the rounded to the nearest part of 10,000.
Theorem 4.2 Let M be a strictly diagonally dominant M-matrix, if


Proof:
Assume 

Note that 
Moreover we conclude the following theorem.
Theorem 4.3 Let M be the M-matrix defined above then
For example

Let 

Now, we will perturb elements inside the diagonal band of the inverse of M-matrix without losing the nonnegativity property. We begin with the 
Theorem 4.4 Let M be a strictly diagonally dominant tridiagonal 
is totally nonnegative for all
Proof:
Let
Be a nonsingular strictly diagonally dominant tridiagonal M-matrix then 
By Lemma 3.5 and Proposition 3.2, we have


By using the formula in Proposition 3.3

Note that a similar result holds for decreasing the element 



We can generalize this result for the other elements of diagonal.
Theorem 4.5 Assume M is a strictly diagonally dominant tridiagonal M-matrix. Then the matrix
is totally nonnegative for all
Proof: Suppose that 




To compute 







Take the case when 


Now suppose 

Suppose that

which contradicts the nonnegativity of
Numerical Example: Let 

The matrices




are TNN matrices.
Note that
References
- McDonald, J.J., Nabben, R., Neumannand, M., Schneider, H. and Tsatsomeros, M.J. (1998) Inverse Tridiagonal Z-Matrices. Linear and Multilinear Algebra, 45, 75-97. http://dx.doi.org/10.1080/03081089808818578
- Berman, A. and Plemmons, R. (1979) Nonnegative Matrices in the Mathenlatical Sciences. Academic, New York.
- Peña, J.M. (1995) M-Matrices Whose Inverses Are Totally Positive. Linear Algebra and Its Applications, 221, 189- 193. http://dx.doi.org/10.1016/0024-3795(93)00244-T
- Ostrowski, A. (1937) Über die Determinanten mit überwiegender Hauptdiagonale. Commentarii Mathematici Helvetici, 10, 69-96. http://dx.doi.org/10.1007/BF01214284
- Minkowski, H. (1900) Zur Theorie der Einheiten in den algebraischen Zahlkörper. Nachrichten von der Königl. Gesellschaft der Wissenschaften und der Georg-Augusts-Universität zu Göttingen Mathematisch-Physikalische Klasse: Fachgruppe II, Nachrichten aus der Physik, Astronomie, Geophysik, Technik, 90-93.
- Minkowski, H. (1907) Diophantische Approximationen. Tuebner, Leipzig. http://dx.doi.org/10.1007/978-3-663-16055-7
- Horn, R. and Johnson, C. (1991) Topics in Matrix Analysis. Cambridge University Press, Cambridge. http://dx.doi.org/10.1017/CBO9780511840371
- Adm, M. and Garloff, J. (2014) Invariance of Total Nonnegativity of a Tridiagonal Matrix under Element-Wise Perturbation. Operators and Matrices, 8, 129-137. http://dx.doi.org/10.7153/oam-08-06
- Ando, T. (1987) Totally Positive Matrices. Linear Algebra and Its Applications, 90, 165-219. http://dx.doi.org/10.1016/0024-3795(87)90313-2
- Pinkus, A. (2010) Totally Positive Matrices. Cambridge Tracts in Mathematics (No. 181). Cambridge University Press, Cambridge.
- Fallat, S.M. and Johnson, C.R. (2011) Totally Nonnegative Matrices. Princeton University Press, Princeton, Oxford. http://dx.doi.org/10.1515/9781400839018
- Adam, M. and Garloff, J. (2013) Interval of Totally Nonnegative Matrices. Linear Algebra and Its Applications, 439, 3796-3806. http://dx.doi.org/10.1016/j.laa.2013.10.021

























