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On Schur Convexity of Some Symmetric Functions
Journal of Inequalities and Applications volume 2010, Article number: 543250 (2010)
Abstract
For and
, the symmetric function
is defined as
, where
are positive integers. In this paper, the Schur convexity, Schur multiplicative convexity, and Schur harmonic convexity of
are discussed. As consequences, several inequalities are established by use of the theory of majorization.
1. Introduction
Throughout this paper, we use the following notation system.
For , and
, let

If then we denote by

Next we introduce some definitions and well-known results.
Definition 1.1.
Let be a set, and a real-valued function
on
is called a Schur convex function if

for each pair of -tuples
and
in
with
, that is,

where denotes the
th largest component of
. A function
is called Schur concave if
is Schur convex.
Definition 1.2.
Let be a set, and a function
is called a Schur multiplicatively convex function on
if

for each pair of -tuples
and
in
with
.
is called Schur multiplicatively concave if
is Schur multiplicatively convex.
Definition 1.3.
Let be a set. A function
is called a Schur harmonic convex (or Schur harmonic concave, resp.) function on
if

for each pair of -tuples
and
in
with
.
Schur convexity was introduced by Schur [1] in 1923 and it has many applications in analytic inequalities [2, 3], extended mean values [4, 5], graphs and matrices [6], and other related fields. Recently, the Schur multiplicative convexity was investigated in [7–9] and the Schur hamonic convexity was discussed in [10].
For and
, the symmetric function
is defined as

where are positive integers.
The aim of this article is to discuss the Schur convexity, Schur multiplicative convexity, and Schur harmonic convexity of the symmetric function .
Lemma 1.4 (see [11]).
Let be a continuous symmetric function. If
is differentiable in
, then
is Schur convex in
if and only if

for all
Lemma 1.5 (see [7]).
Let be a continuous symmetric function. If
is differentiable in
, then
is Schur multiplicatively convex in
if and only if

for all
Lemma 1.6 (see [10]).
Let be a continuous symmetric function. If
is differentiable in
, then
is Schur harmonic convex in
if and only if

for all
Lemma 1.7 (see [12]).
Let and
. If
, then

Lemma 1.8 (see [12]).
Let and
. If
, then

Lemma 1.9 (see [13]).
Suppose that and
If
then

2. Main Result
Theorem 2.1.
The symmetric function is Schur convex, Schur multiplicatively convex, and Schur harmonic convex in
for all
Proof.
According to Lemmas 1.4–1.6 we only need to prove that



for all and
We divided the proof into seven cases.
Case 1.
If and
, then (1.7) leads to




Case 2.
If and
, then (1.7) yields




Case 3.
If ,
, and
, then from (1.7) we clearly see that




Case 4.
If ,
, and
, then (1.7) implies that




Case 5.
If , and
, then (1.7) leads to




Case 6.
If ,
, and
, then (1.7) yields




Case 7.
If ,
, and
, then (1.7) implies




Therefore, inequality (2.1) follows from inequalities (2.5), (2.9), (2.13), (2.17), (2.21), (2.25), and (2.29), inequality (2.2) follows from inequalities (2.6), (2.10), (2.14),(2.18), (2.22), (2.26), and (2.30), and inequality (2.3) follows from inequalities (2.7), (2.11), (2.15), (2.19), (2.23), (2.27), and (2.31).
3. Applications
In this section, we establish several inequalities by use of Theorem 2.1 and the theory of majorization.
It follows from Lemmas 1.7, 1.8, 1.9, and Theorem 2.1 that Theorem 3.1 is obvious.
Theorem 3.1.
If ,
, and
, then

Theorem 3.2.
If ,
,
, and
, then

Proof.
Theorem 3.2 follows from Theorem 2.1 and the fact that

If we take and
in Theorem 3.1(3) and Theorem 3.2, respectively, then we get the following.
Corollary 3.3.
If with
and
then

If we take and
in Theorem 3.1(3) and Theorem 3.2, respectively, then one gets the following.
Corollary 3.4.
If with
and
then

Remark 3.5.
If we take in Corollaries 3.3 and 3.4, then we have

for and
Theorem 3.6.
If , then

Proof.
Theorem 3.6 follows from Theorem 2.1 and (1.7) together with the fact that

If we take in Theorem 3.6, then we have the following.
Corollary 3.7.
If , then

Theorem 3.8.
Let be an
-dimensional simplex in
and let
be an arbitrary point in the interior of
. If
is the intersection point of straight line
and hyperplane
,
then

Proof.
It is easy to see that and
, and these identities imply that

Therefore, Theorem 3.8 follows from Theorem 2.1 and (1.7) together with (3.11).
Theorem 3.9.
Suppose that is a complex matrix, and
are the eigenvalues of
. If
is a positive definite Hermitian matrix, then

Proof.
We clearly see that and




Therefore, Theorem 3.9(1) follows from (1.7), (3.13), and the Schur convexity of , Theorems 3.9(2) and (3) follow from (3.14) and (3.15) together with the Schur multiplitively convexity of
, and Theorem 3.9(4) follows from (3.16) and the Schur harmonic convexity of
.
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Acknowledgments
The research was supported by NSF of China (no. 60850005) and the NSF of Zhejiang Province (nos. D7080080, Y7080185, and Y607128).
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Xia, WF., Chu, YM. On Schur Convexity of Some Symmetric Functions. J Inequal Appl 2010, 543250 (2010). https://doi.org/10.1155/2010/543250
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DOI: https://doi.org/10.1155/2010/543250
Keywords
- Convex Function
- Intersection Point
- Arbitrary Point
- Symmetric Function
- Related Field