2013
DOI: 10.7153/mia-16-25
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Majorization under constraints and bounds on the second Zagreb index

Abstract: Abstract. In this paper we present a theoretical analysis in order to establish maximal and minimal vectors with respect to the majorization order of particular subsets of ℜ n . Afterwards we apply these issues to the calculation of bounds for a topological descriptor of a graph known as the second Zagreb index. Finally, we show how our bounds may improve the results obtained in the literature, providing some theoretical and numerical examples.Mathematics subject classification (2010): 05C35, 05C05, 05C50.

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Cited by 9 publications
(32 citation statements)
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“…In this section we recall some basic notions on majorization, referring for more details to [2] and [19]. In the sequel we denote by [x α 1 1 , x α 1 2 , · · · , x αp p ] a vector in R n with α i components equal to x i , where p i=1 α i = n. If α i = 1 we use for convenience x i instead of x 1 i , while x 0 i means that the component x i is not present.…”
Section: Notations and Preliminaries Results On Majorizationmentioning
confidence: 99%
See 1 more Smart Citation
“…In this section we recall some basic notions on majorization, referring for more details to [2] and [19]. In the sequel we denote by [x α 1 1 , x α 1 2 , · · · , x αp p ] a vector in R n with α i components equal to x i , where p i=1 α i = n. If α i = 1 we use for convenience x i instead of x 1 i , while x 0 i means that the component x i is not present.…”
Section: Notations and Preliminaries Results On Majorizationmentioning
confidence: 99%
“…Notice that the minimal element of the set S a does not necessarily have integer components, while this is not the case for the maximal element. For our purposes it is crucial to find the minimal vector in S a with integer components which can be constructed by the following procedure (see Remark 12 in [2]). Let us consider, for instance, the vector x * (S [h] a ) = a n n which corresponds to the case m 1 ≤ a n ≤ M 2 .…”
Section: Notations and Preliminaries Results On Majorizationmentioning
confidence: 99%
“…It is noteworthy to state that the results in Theorem 2 are tighter than those in Theorem 1 (for more details see [3] and [4]).…”
Section: Notations and Preliminariesmentioning
confidence: 88%
“…Since λ 1 ≥ Q ≥ P , we provide bounds (1) and (2) better than in [7] (see [3] and [4] for more theoretical details).…”
Section: New Bounds For Normalized Laplacian Eigenvaluesmentioning
confidence: 95%
“…The contribution of this paper is along those lines: we derive, through a methodology based on majorization techniques (see [15–17] and [18]), new bounds on the median eigenvalues of the normalized Laplacian matrix. Consequently, given the relation between the normalized Laplacian matrix and the adjacency matrix eigenvalues, we provide some new bounds for the HL -index.…”
Section: Introductionmentioning
confidence: 99%