Next Article in Journal
On Consensus Indices of Triplex Multiagent Networks Based on Complete k-Partite Graph
Next Article in Special Issue
Some New Bennett–Leindler Type Inequalities via Conformable Fractional Nabla Calculus
Previous Article in Journal
Improved LightGBM-Based Framework for Electric Vehicle Lithium-Ion Battery Remaining Useful Life Prediction Using Multi Health Indicators
Previous Article in Special Issue
Reconstructing the Unknown Source Function of a Fractional Parabolic Equation from the Final Data with the Conformable Derivative
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Some Inequalities Related to Jensen-Type Results with Applications

by
Imran Abbas Baloch
1,2,
Aqeel Ahmad Mughal
3,
Absar Ul Haq
4 and
Kamsing Nonlaopon
5,*
1
Abdus Salam School of Mathematical Sciences, GC University, Lahore 54600, Pakistan
2
Higher Education Department, Government Graduate College for Boys Gulberg, Lahore 54600, Pakistan
3
Department of Mathematics and Statistics, University of Lahore, Lahore 54600, Pakistan
4
Department of Natural Sciences and Humanities, University of Engineering and Technology (Narowal Campus), Lahore 54000, Pakistan
5
Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
*
Author to whom correspondence should be addressed.
Symmetry 2022, 14(8), 1585; https://doi.org/10.3390/sym14081585
Submission received: 12 June 2022 / Revised: 15 July 2022 / Accepted: 26 July 2022 / Published: 2 August 2022

Abstract

:
The class of harmonic convex functions has acquired a very useful and significant placement among the non-convex functions, since this class not only reinforces some major results of the class of convex functions, but also has supported the development of some remarkable results in analysis where the class of convex functions is silent. Therefore, many researchers have deployed themselves to explore valuable results for this class of non-convex functions. This paper obtains new discrete inequalities for univariate harmonic convex functions on linear spaces related to a Jensen-type and a variant of the Jensen-type results. Our results are refinements of very important recent inequalities presented by Dragomir and Baloch et al. Furthermore, we provide the natural applications of our results.

1. Introduction

Within the last several decades, the study of mathematical inequalities and their applications has advanced rapidly and exponentially, having a major impact on numerous research fields [1,2]. Notably, convexity may be used to obtain various novel notions concerning mathematical inequalities and their applications [3,4,5]. Among these mathematical inequalities, Jensen’s inequality is one of the most important inequalities enabled by convexity [6,7,8].
Many inequalities are direct results of Jensen’s inequality, such as Holder, Hermite–Hadamard, Ky Fan’s, Young’s inequalities, and so on [4,9]. Jensen’s inequality also played an important part in statistics, with several applications including estimations for different divergences [10,11], as well as several estimations for Zipf–Mandelbrot law [12,13] and Shannon entropy [14]. In 2003, A. McD. Mercer [15] gave a variant of Jensen’s inequality, which hugely influences the theory of inequalities. S.S. Dragomir [16] introduced the discrete Jensen-type inequality for harmonic convex functions (HCF), and I.A. Baloch et al. in [17] presented a variant of the discrete Jensen-type inequality for harmonic convex functions. Further, I.A. Baloch et al. furnished many results as a direct application of discrete Jensen-type and a variant of the discrete Jensen-type inequality for harmonic-convex functions, see for example [18,19,20]. Many researchers are working on harmonic-convex functions and trying to produce remarkable results and applications in various fields, see [21,22,23,24,25,26,27,28,29].
Definition 1.
Give a function f : D R { 0 } R , it is said to be harmonic convex function on D , if
f u v α u + ( 1 α ) v α f v + 1 α f u
holds for all u , v D and α 0 , 1 . Furthermore, if the inequality is reversed, then f is called harmonic concave.
In [16], S.S. Dragomir proved the following result, which is known as Jensen-type inequality for harmonic convex functions.
Theorem 1.
Let D ( 0 , ) be an interval. If f : D R is a harmonic convex function, then
f 1 r = 1 n ω r u r r = 1 n ω r f ( u r )
holds for all u 1 , , u n D and ω r [ 0 , 1 ] with r = 1 n ω r = 1 .
In [17], I.A. Baloch et al. proved the subsequent result:
Theorem 2.
Let [ m , M ] ( 0 , ) be an interval. If f : [ m , M ] R is harmonic convex function, then for any finite sequence ( u r ) r = 1 n [ m , M ] and ω r [ 0 , 1 ] with r = 1 n ω r = 1 , we have
f 1 1 m + 1 M r = 1 n ω r u r f ( m ) + f ( M ) r = 1 n ω r f ( u r ) .
In [30], I.A. Baloch et al. proved the subsequent result:
Theorem 3.
If Φ : D R is harmonic convex function on harmonic convex subset D R { 0 } , then for any finite positive sequence { u r } r = 1 n D and ω r with W n : = r = 1 n ω r > 0 , we have
n min 1 r n { ω r } 1 n r = 1 n Φ ( u r ) Φ 1 1 n r = 1 n 1 u r 1 W n r = 1 n ω r Φ ( u r ) Φ 1 1 W n r = 1 n ω r u r n max 1 r n { ω r } 1 n r = 1 n Φ ( u r ) Φ 1 1 n r = 1 n 1 u r .
This paper is organized as follows: we firstly derive the refinements of Jensen-type and a variant of Jensen-type. Next, we further refine our presented refinements and point out more or less direct consequences of our results. Secondly, we derive refinements of the well-known weighted HGA and an infinite version of weighted HGA as applications. Finally, we discuss the importance, source of motivation and significance of this research for the class of harmonic convex functions.

2. Main Results

In this section, we firstly establish a refinement of the Jensen-type inequality presented in Theorem 1.
Theorem 4.
Let D R { 0 } be an interval. If f : D R is harmonic convex function, then for any finite positive sequence { u r } r = 1 n D and ω r 0 with r = 1 n ω r = 1 , we have
f 1 s = 1 n ω s u s min 1 r n ( 1 ω r ) f 1 ω r s = 1 n ω s u s ω r u r + ω r f ( u r ) 1 n r = 1 n ( 1 ω r ) f 1 ω r s = 1 n ω s u s ω r u r + r = 1 n ω r f ( u r ) max 1 r n ( 1 ω r ) f 1 ω r s = 1 n ω s u s ω r u r + ω r f ( u r ) s = 1 n ω s f ( u s ) .
In particular
f n s = 1 n 1 u s 1 n min 1 r n ( n 1 ) f n 1 s = 1 n 1 u s 1 u r + f ( u r ) 1 n 2 r = 1 n ( n 1 ) f n 1 s = 1 n 1 u s 1 u r + r = 1 n f ( u r ) 1 n max 1 r n ( n 1 ) f n 1 s = 1 n 1 u s 1 u r + f ( u r ) 1 n s = 1 n f ( u s ) .
Proof. 
For any r { 1 , , n } , we have
s = 1 n ω s u s ω r u r = s = 1 s r n ω s u s = s = 1 s r n ω s 1 s = 1 s r n ω s s = 1 s r n ω s u s = ( 1 ω r ) 1 s = 1 s r n ω s s = 1 s r n ω s u s ,
which implies that
s = 1 n ω s u s ω r u r 1 ω r = 1 s = 1 s r n ω s s = 1 s r n ω s u s D
for each r { 1 , , n } , since right side of (7) is a reciprocal of harmonic convex combinations of elements u s D , s { 1 , , n } { r } . Taking the function f on reciprocal of (7) and applying Jensen-type inequality (2), we get successively
f 1 ω r s = 1 n ω s u s ω r u r = f 1 1 s = 1 s r n ω s s = 1 s r n ω s u s 1 s = 1 s r n ω s s = 1 s r n ω s f ( u s ) = 1 1 ω r s = 1 n ω s f ( u s ) ω r f ( u r )
for any r { 1 , , n } , which implies
( 1 ω r ) f 1 ω r s = 1 n ω s u s ω r u r + ω r f ( u r ) s = 1 n ω s f ( u s )
for each r { 1 , , n } .
Utilizing the harmonic convexity of f, we also have
( 1 ω r ) f 1 ω r s = 1 n ω s u s ω r u r + ω r f ( u r ) f 1 ( 1 ω r ) s = 1 n ω s u s ω r u r 1 ω r + ω r u r = f 1 s = 1 n ω s u s
for each r { 1 , , n } .
Taking the minimum over r in (9) and utilizing the fact that
min r { 1 , , n } a r 1 n r = 1 n a r max r { 1 , , n } a r
and then taking maximum over r in (8), we deduce our result (5). □
Theorem 5.
Let f : ( 0 , ) R be a harmonic convex function and u , v ( 0 , ) . If u r : = u v ( 1 α r ) v + α r u with α r [ 0 , 1 ] and ω r 0 , r { 1 , , n } with r = 1 n ω r = 1 , then
f 1 1 u + 1 v r = 1 n ω r u r r = 1 n ω r f 1 1 u + 1 v 1 u r r = 1 n ω r α r f ( u ) + 1 r = 1 n ω r α r f ( v ) f ( u ) + f ( v ) r = 1 n ω r f u r .
Proof. 
By Jensen-type discrete inequality (2), we have
f 1 1 u + 1 v r = 1 n ω r u r = f 1 r = 1 n ω r 1 u + 1 v 1 u r r = 1 n ω r f 1 1 u + 1 v 1 u r = r = 1 n ω r f 1 1 u + 1 v ( 1 α r ) v + α r u u v = r = 1 n ω r f u v ( 1 α r ) u + α r v
which proves the first inequality in (10).
By utilizing harmonic convexity of f, we derive
r = 1 n ω r f u v ( 1 α r ) u + α r v r = 1 n ω r [ α r f ( u ) + ( 1 α r ) f ( v ) ] = r = 1 n ω r α r f ( u ) + 1 r = 1 n ω r α r f ( v )
which proves the second inequality in (10).
Now, again by harmonic convexity of f, we also have
f u v ( 1 α r ) v + α r u ( 1 α r ) f ( u ) + α r f ( v )
for r { 1 , , n } . Multiply this inequality by ω r 0 , r { 1 , , n } and sum over r from 1 to n, then we deduce
r = 1 n ω r f u r r = 1 n ω r [ ( 1 α r ) f ( u ) + α r f ( v ) ] = 1 r = 1 n ω r α r f ( u ) + r = 1 n ω r α r f ( v ) .
Therefore, by (11)
r = 1 n ω r α r f ( u ) + 1 r = 1 n ω r α r f ( v ) = f ( u ) + f ( v ) 1 r = 1 n ω r α r f ( u ) + r = 1 n ω r α r f ( v ) f ( u ) + f ( v ) r = 1 n ω r f u r ,
which proves the last part of inequality in (10). □
Remark 1.
We observe that the inequality (10) is equivalent to the inequality
r = 1 n ω r f u r 1 r = 1 n ω r α r f ( u ) + r = 1 n ω r α r f ( v ) f ( u ) + f ( v ) r = 1 n ω r f 1 1 u + 1 v 1 u r f ( u ) + f ( v ) f 1 1 u + 1 v r = 1 n ω r u r ,
where f : ( 0 , ) R is a harmonic convex function, u , v ( 0 , ) , u r = u v ( 1 α r ) v + α r u with α r 0 , 1 and ω r 0 , r { 1 , , n } with r = 1 n ω r = 1 .
Since the distance between the extreme terms is greater than the distance between internal ones, we can state the following corollary as well:
Corollary 1.
Under the assumptions of Theorem 5, we have
0 r = 1 n ω r α r f ( u ) + 1 r = 1 n ω r α r f ( v ) r = 1 n ω r f 1 1 u + 1 v 1 u r f ( u ) + f ( v ) f 1 1 u + 1 v r = 1 n ω r u r r = 1 n ω r f u r .
Theorem 6.
Under the assumptions of Theorem 5, we also have
f 1 1 u + 1 v r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 1 u + 1 v 1 u r n f 1 1 u + 1 v 1 n r = 1 n 1 u r + f 1 1 u + 1 v r = 1 n ω r u r r = 1 n ω r f 1 1 u + 1 v 1 u r f ( u ) + f ( v ) r = 1 n ω r f ( u r ) .
Proof. 
By the harmonic convexity of f, we have (see [17])
f 1 1 u + 1 v 1 u r + f ( u r ) f ( u ) + f ( v )
for r { 1 , , n } .
If we multiply this inequality by ω r 0 and sum over 1 to n, then we get
r = 1 n ω r f 1 1 u + 1 v 1 u r f ( u ) + f ( v ) r = 1 n ω r f ( u r ) .
If we apply the first inequality in (4) for harmonic convex function Φ ( t ) = f 1 1 u + 1 v 1 t for t [ 0 , 1 ] , we have
0 min 1 r n { ω r } r = 1 n f 1 1 u + 1 v 1 u r n f 1 1 u + 1 v 1 n r = 1 n 1 u r r = 1 n ω r f 1 1 u + 1 v 1 u r f 1 1 u + 1 v r = 1 n ω r u r .
By making the use of (15) and (16), we get the desired result (14). □
We also have: The proof follows by Theorem 6 observing that the difference between the extreme terms is more significant than the difference between the internal ones.
Corollary 2.
With the assumptions of Theorem 5, we have
0 r = 1 n ω r f 1 1 u + 1 v 1 u r f 1 1 u + 1 v r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 1 u + 1 v 1 u r n f 1 1 u + 1 v 1 n r = 1 n 1 u r f ( u ) + f ( v ) r = 1 n ω r f ( u r ) f 1 1 u + 1 v r = 1 n ω r u r .
Theorem 7.
Let f : ( 0 , ) R be a harmonic convex function and u r ( 0 , ) , r { 1 , , n } and a , b R { 0 } with a u r u r a , b u r u r b ( 0 , ) for r { 1 , , n } , then for all λ [ 0 , 1 ] and ω r 0 for r { 1 , , n } with r = 1 n ω r = 1 , we have
f 1 1 λ a + λ b r = 1 n ω r u r r = 1 n ω r f 1 1 λ a + λ b 1 u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r
and
0 ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ a + λ b 1 u r r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r f 1 1 λ a + λ b r = 1 n ω r u r .
Proof. 
By the Jensen’s type inequality (2), we have
f 1 1 λ a + λ b r = 1 n ω r u r = f 1 r = 1 n ω r [ 1 λ a + λ b 1 u r ] = f 1 r = 1 n ω r [ ( 1 λ ) ( 1 a 1 u r ) + λ ( 1 a 1 u r ) ] r = 1 n ω r f 1 ( 1 λ ) ( 1 a 1 u r ) + λ ( 1 a 1 u r ) = r = 1 n ω r f 1 1 λ a + λ b 1 u r ,
which proves the first inequality in (18).
By the harmonic convexity of f
f 1 1 λ a + λ b 1 u r = f 1 ( 1 λ ) ( 1 a 1 u r ) + λ ( 1 b 1 u r ) ( 1 λ ) f 1 1 a 1 u r + λ f 1 1 b 1 u r = ( 1 λ ) f a u r u r a + λ f b u r u r b = f a u r u r a + f b u r u r b λ f a u r u r a + ( 1 λ ) f b u r u r b
for r { 1 , , n } .
If we multiply this inequality by ω r 0 and sum over r from 1 to n, then
r = 1 n ω r f 1 1 λ a + λ b 1 u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r λ f a u r u r a + ( 1 λ ) f b u r u r b ,
which proves the second inequality in (18).
By the harmonic convexity of f, we also have
λ f a u r u r a + ( 1 λ ) f b u r u r b f 1 ( 1 λ ) ( 1 b 1 u r ) + λ ( 1 a 1 u r ) = f 1 1 λ b + λ a 1 u r
for r { 1 , , n } .
If we multiply this inequality by ω r 0 and sum over r from 1 to n, then
r = 1 n ω r [ λ f a u r u r a + ( 1 λ ) f b u r u r b ] r = 1 n ω r f 1 1 λ b + λ a 1 u r
and
r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r λ f a u r u r a + ( 1 λ ) f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r ,
which proves the last inequality in (18).
The inequality (19) follows from the fact that distance between extreme terms is greater then the distance between the internal ones. □
Corollary 3.
Let f : ( 0 , ) R be a harmonic convex function and u r ( 0 , ) , r { 1 , , n } and a , b R { 0 } with a u r u r a , b u r u r b ( 0 , ) for r { 1 , , n } , then for all λ [ 0 , 1 ] and ω r 0 for r { 1 , , n } with r = 1 n ω r = 1 , we have
f 1 a + b 2 a b r = 1 n ω r u r r = 1 n ω r f 1 a + b 2 a b 1 u r 1 2 r = 1 n ω r f a u r u r a + 1 2 r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r
and
0 1 2 r = 1 n ω r f a u r u r a + 1 2 r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r f 1 a + b 2 a b r = 1 n ω r u r .
Now, we give the improvement of (18) as follows:
Corollary 4.
Under assumptions of Theorem 7, we have
f 1 a + b 2 a b r = 1 n ω r u r 1 2 f 1 λ a + 1 λ b r = 1 n ω r u r + f 1 1 λ a + λ b r = 1 n ω r u r 1 2 r = 1 n ω r f 1 1 λ a + λ b 1 u r + r = 1 n ω r f 1 λ a + 1 λ b 1 u r 1 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b 1 2 r = 1 n ω r f 1 λ b + 1 λ a 1 u r + r = 1 n ω r f 1 1 λ b + λ a 1 u r r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r .
Proof. 
If we write (18) for 1 λ instead of λ , we obtain
f 1 λ a + 1 λ b r = 1 n ω r u r r = 1 n ω r f 1 λ a + 1 λ b 1 u r λ r = 1 n ω r f a u r u r a + ( 1 λ ) r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 λ b + 1 λ a 1 u r .
Now, by adding (18) and (23), we obtain
f 1 λ a + 1 λ b r = 1 n ω r u r + f 1 1 λ a + λ b r = 1 n ω r u r r = 1 n ω r f 1 1 λ a + λ b 1 u r + r = 1 n ω r f 1 λ a + 1 λ b 1 u r r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 λ b + 1 λ a 1 u r r = 1 n ω r f 1 1 λ b + λ a 1 u r ,
namely
1 2 f 1 λ a + 1 λ b r = 1 n ω r u r + f 1 1 λ a + λ b r = 1 n ω r u r 1 2 r = 1 n ω r f 1 1 λ a + λ b 1 u r + r = 1 n ω r f 1 λ a + 1 λ b 1 u r 1 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b 1 2 r = 1 n ω r f 1 λ b + 1 λ a 1 u r + r = 1 n ω r f 1 1 λ b + λ a 1 u r ,
which proves the second, the third and the fourth inequalities in (22).
By the harmonic convexity of f
1 2 f 1 λ a + 1 λ b r = 1 n ω r u r + f 1 1 λ a + λ b r = 1 n ω r u r f 1 a + b 2 a b r = 1 n ω r u r ,
which proves the first inequality in (22).
Moreover,
1 2 r = 1 n ω r f 1 λ a + 1 λ b 1 u r + r = 1 n ω r f 1 1 λ a + λ b 1 u r = r = 1 n ω r 1 2 f 1 λ a + 1 λ b 1 u r + 1 2 f 1 1 λ a + λ b 1 u r r = 1 n ω r f 1 a + b 2 a b 1 u r ,
which implies that
r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b 1 2 r = 1 n ω r f 1 λ b + 1 λ a 1 u r + r = 1 n ω r f 1 1 λ b + λ a 1 u r r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r ,
and the last part of (22) is proved. □
Remark 2.
Let f : ( 0 , ) R { 0 } R be harmonic convex. Now, if we take
y r = 1 1 λ a + λ b 1 u r ,
namely
u r = 1 1 λ a + λ b 1 y r ,
then, by (20) we get for ω r 0 for r { 1 , , n } with r = 1 n ω r = 1 that
f 1 ( 2 λ 1 ) b a 2 a b + r = 1 n ω r y r r = 1 n ω r f 1 ( 2 λ 1 ) b a 2 a b + 1 y r ( 1 λ ) r = 1 n ω r f 1 λ ( b a a b ) + 1 y r + λ r = 1 n ω r f 1 ( 1 λ ) ( a b a b ) + 1 y r r = 1 n ω r f 1 λ ( b a a b ) + 1 y r + r = 1 n ω r f 1 ( 1 λ ) ( a b a b ) + 1 y r r = 1 n ω r f 1 ( 2 λ 1 ) b a 2 a b + 1 y r
provided that y r ( 0 , ) and 1 λ ( b a a b ) + 1 y r , 1 ( 1 λ ) ( a b a b ) + 1 y r ( 0 , ) for r { 1 , , n } and λ [ 0 , 1 ] .
For λ = 1 2 , we derive the inequality
f 1 r = 1 n ω r y r r = 1 n ω r f ( y r ) 1 2 r = 1 n ω r f 1 b a 2 a b + 1 y r + 1 2 r = 1 n ω r f 1 a b 2 a b + 1 y r r = 1 n ω r f 1 b a 2 a b + 1 y r + r = 1 n ω r f 1 a b 2 a b + 1 y r r = 1 n ω r f ( y r )
provided that y r ( 0 , ) and 1 λ ( b a a b ) + 1 y r , 1 ( 1 λ ) ( a b a b ) + 1 y r ( 0 , ) for r { 1 , , n } .
From (25), we also obtain
0 1 2 r = 1 n ω r f 1 b a 2 a b + 1 y r + 1 2 r = 1 n ω r f 1 a b 2 a b + 1 y r r = 1 n ω r f ( y r ) r = 1 n ω r f 1 b a 2 a b + 1 y r + r = 1 n ω r f 1 a b 2 a b + 1 y r r = 1 n ω r f ( y r ) f 1 r = 1 n ω r y r
provided that y r ( 0 , ) and 1 λ ( b a a b ) + 1 y r , 1 ( 1 λ ) ( a b a b ) + 1 y r ( 0 , ) for r { 1 , , n } .
Theorem 8.
Let f : ( 0 , ) R be a harmonic convex function and u r ( 0 , ) , r { 1 , , n } and a , b R { 0 } with a u r u r a , b u r u r b ( 0 , ) for r { 1 , , n } , then for all λ [ 0 , 1 ] and ω r 0 for r { 1 , , n } with r = 1 n ω r = 1 , we have
0 ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b f 1 1 λ a + λ b r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 1 λ a + λ b 1 u r n f 1 1 λ a + λ b 1 n r = 1 n 1 u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b f 1 1 λ a + λ b r = 1 n ω r u r .
Proof. 
Using (4), we have
r = 1 n ω r f 1 1 λ a + λ b 1 u r f 1 1 λ a + λ b r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 1 λ a + λ b 1 u r n f 1 1 λ a + λ b 1 n r = 1 n 1 u r .
Therefore,
( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r = ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b r = 1 n ω r f 1 1 λ b + λ a 1 u r + f 1 1 λ a + λ b r = 1 n ω r u r f 1 1 λ a + λ b r = 1 n ω r u r = ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b f 1 1 λ a + λ b r = 1 n ω r u r r = 1 n ω r f 1 1 λ b + λ a 1 u r f 1 1 λ a + λ b r = 1 n ω r u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b f 1 1 λ a + λ b r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 1 λ a + λ b 1 u r n f 1 1 λ a + λ b 1 n r = 1 n 1 u r ( 1 λ ) r = 1 n ω r f a u r u r a + λ r = 1 n ω r f b u r u r b f 1 1 λ a + λ b r = 1 n ω r u r ,
which proves the desired inequality (27). □
Corollary 5.
With the assumption of Theorem 8, we have
0 1 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b r = 1 n ω r f 1 a + b 2 a b 1 u r 1 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b f 1 a + b 2 a b r = 1 n ω r u r min 1 r n { ω r } r = 1 n f 1 a + b 2 a b 1 u r n f 1 a + b 2 a b 1 n r = 1 n 1 u r 1 2 r = 1 n ω r f a u r u r a + r = 1 n ω r f b u r u r b f 1 a + b 2 a b r = 1 n ω r u r .

3. Applications

Let u r , ω r > 0 , r { 1 , , n } with r = 1 n ω r = 1 . Then, the following inequality is well-known in the literature as the weighted Harmonic–Geometric–Arithmetic (HGA) mean inequality:
1 r = 1 n ω r u r r = 1 n u r ω r r = 1 n ω r u r .
  • The equality holds in (30) if and only if u 1 = = u n . The inequality (30) was nicely proved in [31].
    By applying the inequality (5) for harmonic convex function f ( u ) = ln u , u ( 0 , ) and performing the necessary calculations, we obtain the following refinement of the first inequality of (30):
    1 r = 1 n ω r u r min 1 s n 1 ω s r = 1 n ω r u r ω s u s 1 ω s . u s ω s s = 1 n 1 ω s r = 1 n ω r u r ω s u s 1 ω s . u s ω s 1 n max 1 s n 1 ω s r = 1 n ω r u r ω s u s 1 ω s . u s ω s r = 1 n u r ω r .
  • For I = [ a , b ] and u r I , ( r 1 ) with ω r > 0 such that r = 1 ω r u r , affine combination a + b r = 1 ω r u r and ( a 1 + b 1 r = 1 ω r u r 1 ) 1 converges in I, the following result was proved in [31] as
    a 1 + b 1 r = 1 ω r u r 1 1 a b r = 1 u r ω r a + b r = 1 ω r u r .
    This inequality was firstly proved by Pavić in [32] without considering the class of harmonic convex functions. By applying the inequality (10) for harmonic convex function f ( u r ) = ln u r , u r I = [ a , b ] ( 0 , ) and performing the necessary calculations with assumption that all infinite sum converge, we have the following refinement of first inequality (32).
    a 1 + b 1 r = 1 ω r u r 1 1 r = 1 ( a 1 + b 1 u r 1 ) ω r a r = ω r α r b 1 r = 1 ω r α r a b r = 1 u r ω r .

4. Conclusions

Jensen-type and a variant of Jensen-type inequalities are dominant among numerous results for the class of harmonic convex functions, which gave fascinating consequences in the field of mathematical inequalities, for example smart, shorter and easy proofs of Hölder, weighted HGA and infinite version weighted HGA inequalities. In addition, this class also provided sharp bounds, refinements in inequalities and solved definite integrals, which were having no or tedious analytical solutions. This advancement in analysis with the class of harmonic convex functions is strong source of motivation for further development in this area. Keeping in view the significance of the class of harmonic convex functions, we presented several refinements of Jensen-type and variants of Jensen-type inequalities. Further, we gave a refinement of weighted HG inequality and a refinement of the infinite version weighted HG inequality as applications of our main results. We hope techniques and consequences of this article will inspire researchers to explore more interesting follow-ups in this area.

Author Contributions

Conceptualization, I.A.B.; funding acquisition, K.N.; investigation, I.A.B., A.A.M., A.U.H. and K.N.; methodology, I.A.B., A.A.M., A.U.H. and K.N.; validation, I.A.B., A.A.M., A.U.H. and K.N.; visualization, I.A.B., A.A.M., A.U.H. and K.N.; writing—original draft, I.A.B. and K.N.; writing—review and editing, K.N. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the Higher Education Commission of Pakistan. This research was supported by the Fundamental Fund of Khon Kaen University, Thailand.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No data were used to support this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Borwein, J.; Lewis, A. Convex Analysis and Nonlinear Optimization: Theory and Examples; Springer: New York, NY, USA, 2000. [Google Scholar]
  2. Cloud, M.J.; Drachman, B.C.; Lebedev, L.P. Inequalities with Applications to Engineering; Springer: Cham, Switzerland; Heidelberg, Germany; New York, NY, USA; Dordrecht, The Netherlands; London, UK, 2014. [Google Scholar]
  3. Khan, A.M.; Wu, S.H.; Ullah, H.; Chu, Y.-M. Discrete majorization type inequalities for convex functions on rectangles. J. Inequal. Appl. 2019, 2019, 1–18. [Google Scholar]
  4. Niculescu, C.P.; Persson, L.E. Convex Functions and Their Applications: A Contemporary Approach, 2nd ed.; CMS Books in Mathematics Vol. 23; Springer: New York, NY, USA, 2018. [Google Scholar]
  5. Ullah, H.; Adil Khan, M.; Pečarić, J. New bounds for soft margin estimator via concavity of Gaussian weighting function. Adv. Differ. Equ. 2020, 2020, 1–10. [Google Scholar] [CrossRef]
  6. Furuichi, S.; Moradi, H.R.; Zardadi, A. Some new Karamata type inequalities and their applications to some entropies. Rep. Math. Phys. 2019, 84, 201–214. [Google Scholar] [CrossRef] [Green Version]
  7. Pečarić, J.; Perić, J. New improvement of the converse Jensen inequality. Math. Inequal. Appl. 2018, 21, 217–234. [Google Scholar]
  8. Sababheh, M.; Moradi, H.R.; Furuichi, S. Integrals refining convex inequalities. Bull. Malays. Math. Sci. Soc. 2020, 43, 2817–2833. [Google Scholar] [CrossRef]
  9. Deng, Y.; Ullah, H.; Khan, A.M.; Iqbal, S.; Wu, S. Refinements of Jensen’s inequality via majorization results with applications in the information theory. J. Math. 2021, 2021, 1951799. [Google Scholar] [CrossRef]
  10. Ansari, I.; Khan, K.A.; Nosheen, A.; Pečarić, D.; Pečarić, J. Some inequalities for Csiszar divergence via theory of time scales. Adv. Differ. Equ. 2020, 2020, 698. [Google Scholar] [CrossRef]
  11. Horvath, L.; Pečarić, D.; Pečarić, J. Estimations of f- and Renyi divergences by using a cyclic refinement of the Jensen’s inequality. Bull. Malays. Math. Sci. Soc. 2019, 42, 933–946. [Google Scholar] [CrossRef]
  12. Khan, K.A.; Al-sahwi, Z.M.; Chu, Y.-M. New estimations for Shannon and Zipf-Mandelbrot entropies. Entropy 2018, 20, 608. [Google Scholar] [CrossRef] [Green Version]
  13. Khan, K.A.; Pečarić, D.; Pečarić, J. On Zipf-Mandelbrot entropy. J. Comput. Appl. Math. 2019, 346, 192–204. [Google Scholar] [CrossRef]
  14. Khan, K.A.; Pečarić, D.; Pečarić, J. Bounds for Shannon and Zipf-mandelbrot entropies. Math. Methods Appl. Sci. 2017, 40, 7316–7322. [Google Scholar]
  15. Mercer, A.M.D. A variant of Jensen’s inequality. J. Inequalities Pure Appl. Math. 2003, 4, 73. [Google Scholar]
  16. Dragomir, S.S. Inequalities of Jensen type for HA-convex function. An. Univ. Oradea Fasc. Mat. 2020, 27, 103–124. [Google Scholar]
  17. Baloch, I.A.; Mughal, A.H.; Chu, Y.-M.; Haq, A.U.; Sen, M.D.L. A variant of Jensen-type inequality and related results for harmonic convex functions. AIMS Math. 2020, 5, 6404–6418. [Google Scholar] [CrossRef]
  18. Mughal, A.A.; Afzal, D.; Abdeljawad, T.; Mukheimer, A.; Baloch, I.A. Refined estimates and generalization of some recent results with applications. AIMS Math. 2021, 6, 10728–10741. [Google Scholar] [CrossRef]
  19. Baloch, I.A.; De La Sen, M.; İşcan, İ. Characterizations of classes of harmonic convex functions and applications. Int. J. Anal. Appl. 2019, 17, 722–733. [Google Scholar]
  20. Baloch, I.A.; Chu, Y.-M. Petrović-type inequalities for harmonic h-convex functions. J. Funct. Spaces 2020, 2020, 3075390. [Google Scholar]
  21. Gao, W.; Kashuri, A.; Butt, S.I.; Tariq, M.; Aslam, A.; Nadeem, M. New inequalities via n-polynomial harmonically exponential type convex functions. AIMS Math. 2020, 5, 6856–6873. [Google Scholar] [CrossRef]
  22. Tariq, M.; Butt, S.I.; Butt, S.I. Some Ostrowski type integral inequalities via generalized harmonic convex functions. Open J. Math. Sci. 2021, 5, 200–208. [Google Scholar] [CrossRef]
  23. Ji, A.C.; Liu, W.M.; Song, J.L.; Zhou, F. Dynamical creation of fractionalized vortices and vortex lattices. Phys. Rev. Lett. 2008, 101, 010402. [Google Scholar] [CrossRef] [Green Version]
  24. Liang, Z.X.; Zhang, Z.D.; Liu, W.M. Dynamics of a Bright Soliton in Bose-Einstein Condensates with Time-Dependent Atomic Scattering Length in an Expulsive Parabolic Potential. Phys. Rev. Lett. 2005, 94, 050402. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Butt, S.I.; Yousaf, S.; Asghar, A.; Khan, K.A.; Moradi, H.R. New fractional Hermite-Hadamard-Mercer inequalities for harmonically convex function. J. Funct. Spaces. 2021, 2021, 5868326. [Google Scholar] [CrossRef]
  26. Butt, S.I.; Agarwal, P.; Yousaf, S.; Guirao, J.L. Generalized fractal Jensen and Jensen-Mercer inequalities for harmonic convex function with applications. J. Inequal. Appl. 2022, 2022, 1. [Google Scholar] [CrossRef]
  27. Butt, S.I.; Yousaf, S.; Khan, K.A.; Matendo Mabela, R.; Alsharif, A.M. Fejer-Pachpatte-Mercer-type inequalities for harmonically convex functions involving exponential function in kernel. Math. Probl. Eng. 2022, 2022, 7269033. [Google Scholar] [CrossRef]
  28. Akhtar, N.; Awan, M.U.; Javed, M.Z.; Rassias, M.T.; Mihai, M.V.; Noor, M.A.; Noor, K.I. Ostrowski type inequalities involving harmonically convex functions and applications. Symmetry 2021, 13, 201. [Google Scholar] [CrossRef]
  29. Ali, R.S.; Mukheimer, A.; Abdeljawad, T.; Mubeen, S.; Ali, S.; Rahman, G.; Nisar, K.S. Some new harmonically convex function type generalized fractional integral inequalities. Fractal Fract. 2021, 5, 54. [Google Scholar] [CrossRef]
  30. Mughal, A.A.; Almusawa, H.; Haq, A.U.; Baloch, I.A. Properties and bound of functional related to Jensen-type Inequalities. J. Math. 2021, 2021, 5561611. [Google Scholar] [CrossRef]
  31. Baloch, I.A.; Mughal, A.A.; Chu, Y.-M.; Haq, A.U.; Sen, M.D.L. Improvement and generalization of some results related to the class of harmonically convex functions and applications. Int. J. Math. Comput. Sci. 2021, 22, 282–294. [Google Scholar]
  32. Pavic, Z. The Jensen-Mercer Inequality with Infinite Convex Combinations. Math. Sci. Appl. E-Notes 2019, 7, 19–27. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Baloch, I.A.; Mughal, A.A.; Haq, A.U.; Nonlaopon, K. Some Inequalities Related to Jensen-Type Results with Applications. Symmetry 2022, 14, 1585. https://doi.org/10.3390/sym14081585

AMA Style

Baloch IA, Mughal AA, Haq AU, Nonlaopon K. Some Inequalities Related to Jensen-Type Results with Applications. Symmetry. 2022; 14(8):1585. https://doi.org/10.3390/sym14081585

Chicago/Turabian Style

Baloch, Imran Abbas, Aqeel Ahmad Mughal, Absar Ul Haq, and Kamsing Nonlaopon. 2022. "Some Inequalities Related to Jensen-Type Results with Applications" Symmetry 14, no. 8: 1585. https://doi.org/10.3390/sym14081585

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop