On improvements of Fischer’s inequality and Hadamard’s inequality for -matrices
© Li; licensee Springer. 2013
Received: 16 May 2013
Accepted: 9 September 2013
Published: 7 November 2013
In this paper, the class of -matrices, which includes positive definite matrices, totally positive matrices, M-matrices and inverse M-matrices, is first introduced and the refinements of Fischer’s inequality and Hadamard’s inequality for -matrices are obtained. Some previous well-known results for totally nonnegative matrices can be regarded as the special case of this paper.
All matrices considered in this paper are real. For an matrix , the submatrix of A lying in rows indexed by α and the columns indexed by β will be denoted by . If , then the principal submatrix is abbreviated to . For any , let denote the complement of α relative to , and let denote the cardinality of α. If , we define . We use for the symmetric group on .
Fischer: , for ;
Koteljanskii: , for .
The study of multiplicative principal minor inequalities has been actively going on for many years, many authors have done various wonderful works on this topic, see [7–11]. In , Zhang and Yang improved Hadamard’s inequality for totally nonnegative matrices as follows:
Hadamard’s inequality for some subclasses of -matrices is an important inequality in matrix analysis, inequality (1.1) is the generalization of Hadamard’s inequality for totally nonnegative matrices. It is a noticeable problem to generalize inequality (1.1) for totally nonnegative matrices to other classes of matrices. In this paper we give some new upper bounds of Fischer’s inequality and Hadamard’s inequality for a subclass of -matrices and extend the corresponding results due to Zhang and Yang (see ).
2 Some lemmas
To avoid triviality, we always assume . We will need important Sylvester’s identity for determinants (see ).
Lemma 2.1 
For convenience, we introduce the following definition.
Definition 2.1 A -matrix (P-matrix) A is called a -matrix (K-matrix) if every principal submatrix of A satisfies Koteljanskii’s inequality.
Obviously, each principal submatrix of a -matrix (K-matrix) is a -matrix (K-matrix). Of course, each of the matrices PD, TP, M and is a K-matrix, the totally nonnegative matrices are -matrices. In fact, an evident necessary and sufficient condition for a K-matrix was given in .
Lemma 2.2 
A P-matrix satisfies Koteljanskii’s inequality if and only if it is 1-minor symmetric.
Lemma 2.3 If an matrix is a -matrix, then for .
This completes the proof. □
Lemma 2.4 Let A be a K-matrix, B be the Sylvester matrix of A associated with , then B is a K-matrix.
this means that B is a P-matrix.
By Lemma 2.2 and (2.2), we conclude that B is 1-minor symmetric, therefore B is a K-matrix. □
hence inequality (2.3) follows. □
3 Main results
In this section, we give some new upper bounds for Fischer’s inequality and Hadamard’s inequality, and extend the corresponding results due to Zhang and Yang (see ).
where and .
Combining (3.6) and (3.7), we obtain inequality (3.1). □
therefore inequality (3.1) holds.
Let (), by Theorem 3.1 and the induction, we can obtain the following conclusion.
If is a totally nonnegative matrix with , Corollary 3.2 is certainly valid, so Corollary 3.2 is the generalization of Theorem 3 in .
Proof If A is singular, by Lemma 2.3 and Lemma 2.5, we know (3.8) is valid. If A is a nonsingular -matrix, then A is a K-matrix. We suppose that A is a K-matrix in the following.
If , then equality in (3.8) holds. If , then first we prove the following conclusion:
Case 1. If . For any , by Lemma 2.3, we know that (3.9) certainly holds.
Case 2. If . Let , then , it is easy to see that (3.9) is true even with the equality sign for . Now we assume that .
which is a contradiction to (3.14), therefore (3.9) holds.
therefore (3.8) holds. □
If is a totally nonnegative matrix, Theorem 3.3 is certainly valid too, so Theorem 3.3 is the generalization of Theorem 4 in .
therefore inequality (3.8) holds.
By Corollary 3.2 and Theorem 3.3, we get the following result.
If A is a totally nonnegative matrix, Corollary 3.4 is valid, so we obtain the result in .
Corollary 3.5 
The author expresses his deep gratitude to the referees for their many very valuable suggestions and comments. The research of this paper was supported by the Natural Science Foundation of Shandong Province of China (ZR2010AL017).
- Fallat SM, Johnson CR: Determinantal inequalities: ancient history and recent advances. Contemp. Math. 2000, 259: 199–212.MathSciNetView ArticleGoogle Scholar
- Ando T: Totally positive matrices. Linear Algebra Appl. 1987, 90: 165–219.MATHMathSciNetView ArticleGoogle Scholar
- Carlson D: Weakly sign-symmetric matrices and some determinantal inequalities. Colloq. Math. 1967, 17: 123–129.MATHMathSciNetGoogle Scholar
- Gantmacher FR, Krein MG: Oszillationsmatrizen, Oszillationskerne und kleine Schwingungen Mechanischer Systeme. Akademie Verlag, Berlin; 1960.MATHGoogle Scholar
- Johnson CR, Smith RL: Almost principal minors of inverse M -matrices. Linear Algebra Appl. 2001, 337: 253–265. 10.1016/S0024-3795(01)00352-4MATHMathSciNetView ArticleGoogle Scholar
- Koteljanskii DM: A property of sign-symmetric matrices. Usp. Mat. Nauk 1953, 8: 163–167. (in Russian). English transl.: Am. Math. Soc. Transl. 27, 19–24 (1963)Google Scholar
- Chen S: Inequalities for M -matrices and inverse M -matrices. Linear Algebra Appl. 2007, 426: 610–618. 10.1016/j.laa.2007.05.040MATHMathSciNetView ArticleGoogle Scholar
- Elhashash A, Szyld DB: Generalizations of M -matrices which may not have a nonnegative inverse. Linear Algebra Appl. 2008, 49: 2435–2450.MathSciNetView ArticleGoogle Scholar
- Fallat SM, Gekhtman MI: Multiplicative principal-minor inequalities for totally nonnegative matrices. Adv. Appl. Math. 2003, 30: 442–470. 10.1016/S0196-8858(02)00506-7MATHMathSciNetView ArticleGoogle Scholar
- Fallat SM, Johnson CR: Hadamard powers and totally positive matrices. Linear Algebra Appl. 2007, 423: 420–427. 10.1016/j.laa.2007.01.012MATHMathSciNetView ArticleGoogle Scholar
- Zhang X, Yang S: An improvement of Hadamard’s inequality for totally nonnegative matrices. SIAM J. Matrix Anal. Appl. 1993, 14: 705–711. 10.1137/0614050MATHMathSciNetView ArticleGoogle Scholar
- Horn RA, Johnson CR: Matrix Analysis. Cambridge University Press, New York; 1985.MATHView ArticleGoogle Scholar
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