Probl. Anal. Issues Anal. Vol. 6(24), No. 2, 2017, pp. 25-41
25
DOI: 10.15393/j3.art.2017.3790
UDC 517.51
S. S. Dragqmir
INEQUALITIES OF HERMITE-HADAMARD TYPE FOR HG-CONVEX FUNCTIONS
Abstract. Some inequalities of Hermite-Hadamard type for HG -convex functions defined on positive intervals are given. Applications for special means are also provided.
Key words: convex functions, integral inequalities, HG-convex functions
2010 Mathematical Subject Classification: 26D15, 25D10
1. Introduction. Following [4] (see also [26]) we say that the function f : I C R \ {0} ^ R is HA-convex if
for all x,y E I and t E [0,1]. If the inequality in (1) is reversed, then f is said to be HA-concave.
If I C (0, to) and f is convex and nondecreasing function then f is HA-convex and if f is HA-convex and nonincreasing function then f is convex.
If [a, 6] C I C (0, oo) and if we consider the function g : [1, 1] ^ R, defined by g (t) = f (1), then we can state the following fact [4]:
Lemma 1. The function f is HA-convex on [a, 6] if and only if g is convex in the usual sense on [1,1].
Therefore, as examples of HA-convex functions we can take f (t) = = g (1), where g is any convex function on [1,1].
In the recent paper [16] we obtained the following characterization result as well:
©Petrozavodsk State University, 2017
[MglHl
(1)
Lemma 2. Let f, h : [a, b] C (0, to) ^ R be so that h (t) = tf (t) for t E [a, b]. Then f is HA-convex on the interval [a, b] if and only if h is convex on [a, b].
Following [4] (see also [26]) we say that the function f : I C R \ {0} ^ ^ (0, to) is HG-convex if
f (ix+fr^) *f (x)]1-t f (y)]t (2)
for all x,y E I and t E [0,1]. If the inequality in (2) is reversed, then f is said to be HG-concave.
By the geometric-mean - arithmetic mean inequality we have that any HG-convex function is HA-convex. The converse is obviously not true.
We observe that f : I C R \ {0} ^ (0, to) is HG-convex if and only if the function ln f : I C R \ {0} ^ R is HA-convex on I. Using Lemmas 1 and 2 we have:
Theorem 1. Let f : [a, b] C (0, to) ^ (0, to) and define the associated functions Gf : [ 1, a ] ^ R defined by Gf (t) = ln f (1) and Hf : [a, b] C C (0, to) ^ R defined by Hf (t) = t ln f (t). Then the following statements are equivalent:
(i) The function f is HG-convex on [a, 6] ;
(ii) The function Gf is convex on [1, a];
(iii) The function Hf is convex on [a, b].
For a convex function h : [c, d] ^ R, the following inequality is well known in the literature as the Hermite-Hadamard inequality
d
, (c + d\ 1 ,, , h (c) + h (d)
h(—) * ir-/h (t) dt * ^-V0. (3)
c
For related results, see [1] - [10], [12]-[28].
Motivated by the above results, we establish in this paper some inequalities of Hermite-Hadamard type for HG-convex functions defined on positive intervals. Applications for special means are also provided. 2. Main Results. The following result holds.
Theorem 2. Let f : [a, b] C (0, to) ^ (0, to) be an HG-convex function on the interval [a, b]. Then for any A E [0,1] we have the inequalities
A —\*
Ma + b ' *
j. , 2ab
(1 - A) a + (A + 1) b
1-A
j. , 2ab
(2 - A) a + Ab,
A
<
< exp
i b
' ab /ln f (t)
b - a J t2
a
dt I <
<1 f
ab
(1 - A) a + Ab
[f (a)]1 [f (b)]A < Vf (a) f (b).
If we take A = 1 in (4), then we get
(4)
f( —1 <a fi —W — I <
a + b < \ Ma + 3b / f V 3a + b
< exp
ab ba
ln f (t) t2
dt I <
<1 f
2ab a + b
Vf (a) f (b) < Vf (a) f (b).
(5)
The identric mean I (a, 6) for two distinct positive numbers a, 6 is defined by
i
1 / b-a I (a,b);=i(ai
while the logarithmic mean is defined by
T ( n 6 - a
L (a, 6) :=
ln 6 — ln a
Theorem 3. Let f : [a, 6] C (0, to) ^ (0, to) be an HG-convex function on the interval [a, 6]. Then
(
f (L (a,b)) < exP
1
ba
(L(g,b)-g)b (b-L(g,b))g
ln f (t) dt | < [f (b)] (b a) L(a,b) [f (a)] (b a)L (a,b)
(6)
If we write the classical Hermite-Hadamard inequality for the function Hf that is convex on [a, 6] when f : [a, 6] C (0, to) ^ (0, to) is an HG-convex function on [a, 6] and perform the required calculations, we get:
b
b
Theorem 4. Let f : [a, b] C (0, to) ^ (0, to) be an HG-convex function on the interval [a, b]. Then we have
f
a + b
a + b
— exp
/ ! Ï
ba
t ln f (t) dtl < V [f (b)]b [f (a)]a. (7)
We have the reverse inequalities as well:
Theorem 5. Let f : [a, b] C (0, to) ^ (0, to) be an HG-convex function on the interval [a, b]. Then we have
exp I ^ I f dt
1 <
f I 2ab f \ a+b
<
(8)
and
< exH 8
f- (b) b2_ f+ (a) a2
Lf (b)
f (a)
1
Vf (a) f (b)
ex^ baba/
f dt
b — a ab
<
(9)
< exp -
f- (b),2 f+ (a) a2
f (b)
b2
f (a)
b — a ab
The following related result also holds:
Theorem 6. Let f : [a, b] С (0, то) ^ (0, то) be an HG-convex function on the interval [a, b]. Then we have
1
[f (a)]a [f (b)]b
exp bi/1 ln f (t) dt
<
- Vf (a) У
8 (b-a)
I 1 (b ) f bf- (b) af+ (a)
e !(b—a)lnr— fâT
2
2
and
exp( ft ln f (t) dt
1 < V 1 a+b - <
[f ()]
/ f (6) \ 8 (b"a) /1(6 ) / f (6) af+ (a)\\ (11)
H/Mi ex\8 (6 — a)l TW — "T(arJJ • (11)
From a different perspective we have:
Theorem 7. Let f : [a, 6] C (0, to) ^ (0, to) be an HG-convex function on the interval [a, 6]. Then
exp
( b _
rtb /"ln f (t) 1 / a(b-x) b(x-a)
1 f (t) dt I < Vf (x) [f (b)] Xb-) [f (a)] (12)
b - a t2
\ a
for any x G [a, b].
If we take in (12), x = a2b, then we get from (12) that
exp
'jk ./ f dt ) < // (^) ff (b)]a+b ff („)] A. (13)
3. Proofs. In [15], in order to improve Iscan's inequality [26] for HA-convex functions g : [a, 6] C (0, to) ^ R,
b
( 2a6 \ a6 f g (t) , g (a) + g (6) ,„
g brW < ^ rwdt < ^^^ir^, (14)
we obtained the following result:
/ 2a6 \ / 2a6 \
»U + jJ < (1 — A) H (1 — A) a r(A + 1) b) +
b
A / 2a6 \ a6 fa (t) ,
+Ag —-n-— < ,- ^dt <
\ (2 — A) a + A6 y < 6 — a 7 t2 <
1
< -*2
g
ab
(1 - A) a + Ab
+ (1 - A) g (a) + Ag (b)
<
<
g(a) + g(b) 2
(15)
where A E [0, 1] .
Now, if f : [a, b] C (0, to) ^ (0, to) is an HG-convex function on the interval [a, b], then g := ln f is HA-convex on [a, b], and by (15) we get
2ab 2ab
flaTb) * (1 - A)lnf((1 - A)a + (A +1)b
+
1
< -*2
+A ln f ln f
2ab
(2 - A) a + Ab J ~ b - a ab
ab f ln f (t) ,
< -- / dt <
t2
(1 - A) a + Ab
ln f (a) + ln f (b)
+ (1 - A) ln f (a) + A ln f (b)
<
<
2
that is equivalent to
ln
f
2ab
(1 - A) a + (A + 1) b
2ab
ln f ( -- ) *
f
a+b
1-A
2ab
(2 - A) a + Ab
(16)
<
* f dt * W /
a
ab
(1 - A) a + Ab
[f (a)]1-A [f (b)]A *
* ln Vf (a) f (b),
and by taking the exponential we get the desired result (4). We have the following result for HA-convex functions [15]:
Lemma 3. Let g : [a, b] C (0, to) ^ R be an HA-convex function on the interval [a, b]. Then
g (L (a, b)) *
1
ba
g (x) dx *
(L (a, b) - a) bg (b) + (b - L (a, b)) ag (a)
(b - a) L (a, b)
b
A
b
b
If f : [a, b] С (0, то) ^ (0, to) is an HG-convex function on the interval [a, b], then g := ln f is HA-convex on [a, b], and by (17) we have
b
ln f (L (a, b)) t ln f (x) dx <
ba
(L (a, b) - a) b ln f (b) + (b - L (g,b)) a ln f (a) _
_ (b — a) L (a, b)
((L(a,b)-a)b (b-L(a,b))a \
[f (b)] (b a)L(a,b) [f (a)] (b a) L(a,b) \ . (1g)
By taking the exponential in (18) we get the desired result (6).
We use the following results obtained by the author in [10] and [11]:
Lemma 4. Let h : [a, ß] — R be a convex function on [a, ß]. Then we have the inequalities
ß
0 < h (a) + h (ß) — ß—^/h (t) dt < 1 [hi. (ß) — h+ (a)] (ß — a) (19)
a
and
ß
0 < / h (t) dt — h^^) < g [hi (ß) — h+ (a)] (ß — a). (20)
a
The constant 8 is best possible in (19) and (20).
If i : [a, b] C (0, to) —> R is an HA-convex function on the interval [a, b], then the function g : [1, 1] — R, g (s) = i (1) , is convex on [1,1] . Now, by (19) and (20) we have
0 - g Ш + g (bi — — Ig (t) dt -2 a — ь J
1
< -< 8
11
a — gn b
a b> (21)
a
b
and
0 <
— 1
a
g (t) dt - g( i+i I —
We also have
and then
1
< -— 8
g- i - g+n
11
g± « =^ (1) (-h)
g'_ Q) = -t+ (a) a2 and g^ (i) = -t- (b) b2.
From (21) and (22) we have
(22)
and
£(a)±M_ft(i dS<
b — a
— 1 [/_ (b)b2 - (a) a2](
ab 1 2ab
0 — t- t - ds - N -r I —
b — a / \s J \a ± b
— 1 (b) b2 - 4 (a) a2](
(23)
(24)
If we change the variable 1 = u, then ds = — tr and (23) and (24) can be written as
b
0< I (a) + I (6) a6 j £Jt) dt <
b - a ./ t2
ba
— 1 ['- (b) b2 - (a) a2](
(25)
1
b
b
a
and
0 <
ab [£ (t) / 2ab
b - a J t2
a
a + b, ba
<
< 1 [C- (b)b2 - 4 (a) a2](
(26)
If f : [a, b] C (0, to) — (0, to) is an HG-convex function on the interval [a, b], then i := ln f is HA-convex on [a, b], and by (25) and (26) we have
o < in vrwrn - f dt <
1
< -< 8
f- (b) b2_ f+ (a) a2 f (b) b f (a)
b — a ab
(27)
and
0 /fdt - inff Jit I <
b - a J t2
a
1
< -< 8
f- (b) b2 _ f+ (a) a2
Lf (b)
f (a)
a + b
b - a ab
(28)
and the Theorem 5 is proved.
If f : [a, b] C (0, to) ^ (0, to) is an HG-convex function on the interval [a, b], then Hf is convex on [a, b] and by (19) and (20) we have after appropriate calculations
1
< -< 8
0 < in Vf (a)]a [f (b)]b - b-^/t in f (t) dt <
a
bf 1 (b) , , , , af+ (a)
in f (b) +
f (b)
(b - a) =
= m( fi)
8 (b-a)
1
f (a)
bf- (b) af; (a)
+ 8 (b - aH f (b) f (a)
b
and
0
6a
t ln f (t) dt — ln
a + 6
a + b -2
<
( f (6) x 1 (b-g) +1 / 6f- (6) af; (a)
< htmj r1(6—a)
f (6) f (a)
These inequalities are equivalent to
(
0 ln
V[f (a)]1 [f (6)]b
expi b—ftlnf (t) dtj^
<
ln
and
ln
(¿(6)x 8 (b"a) exp (1 (6 - a) ( f-^ - af±ja) Vf (a J exH8(6 f(6) f (a)
0 ln
exp 1 ln f (t) dt
)] a+b
g+bM
[f №)]
V
<
/
/f (6)A Vf (a)7
8 (b-g)
I 1(h ^ f (6) af; (a)
e 8(6—a)bw~— fa)"
and by taking the exponential we get the desired results (10) and (11). The following lemma is of interest in itself:
Lemma 5. Let g : [a, 6] C (0, to) ^ R be a HA-convex function on the interval [a, 6]. Then
1 fg (6) a (6 — x)+ g (a) 6 (x — a)+ xg ^ ^^/g^dy (29)
2x
6a
6 - a y2
for any x E [a, 6] •
b
1
2
Proof. Since h (t) = tg (t) for t E [a, 6] is convex, then by the gradient inequality for convex functions we have
xg (x) — yg (y) > (g (y) + yg- (y^ (x — y)
for any x, y E (a, 6) • This is equivalent to
xg (x) — xg (y) > yg- (y) (x — y) (30)
for any x, y E (a, 6) •
From (30) we have, by division with xy2 > 0, that
~2 o (x) — ^ o (y) > ^ (1 — ^)
y2 y2 y x
for any x, y E (a, 6) •
Taking the integral mean over y we have
b b
g (x) —^ / 4 — / ^ dy >
b — a J y2 b — a J y2
a
b / ь
>7-^ / g-(y)dy - / g- (y) dy
b — a J У xb — a J
that is equivalent to
b
g(x) 1 f g (y) , . ~ar — b—~aj dy>
>
ba
g(b) g(a) b
+
g (y)
dy
1 g(b) — g(a)
x
ba
ba
g(b) g(a) b
a
+
ba
g (yK 1 g(b) — g(a)
-dy---Г-
y2 x b — a
b
1
2
У
b
1
1
for any x E (a, b). This can be written as
b
1 g(b) -g(a) 1 f g(b) g(aA > 2 j" ^Mdy - g(x)
— - ■ - —
x b - a b - a b a b - a y2 ab
a
or as
b
2ba
b x x a
g(b) —r- + g(a)-
xb ax
+> > ¡m. dy.
ab b - a y2
This is equivalent to the desired result (29). □
If f : [a, b] C (0, to) ^ (0, to) is an HG-convex function on the interval [a, b], then g := ln f is HA-convex on [a, b], and by (29) we have
1 fa(b-x)lnf (b) + b(x-a)lnf (a) + xlnf (xA >
2x b a
b
> a^ ¡fri dy
b - a J y2
for any x E [a, b].
This is clearly equivalent to
b
/ / a(b-x) b(x-a) .-\ ab i ln f (y)
ln^V[f (b)] ^ [f (a)]« f)J > — j dy (31)
a
for any x E [a, b] .
If we take the exponential in (31), then we get the desired result (12). 4. Applications. Consider the function f : [a, b] C (0, to) ^ (0, to), f (t) = t. Using the geometric mean - harmonic mean inequality, we have
f (-1 =-x^^ * x1-ty* = [f (x)]1-t [f (y)]* ,
J Vtx + (1 - t) y) tx + (1 - t) y * y L,/ WJ u vyyj '
which shows that f is HG-convex on [a, b]. We need the following integrals
b b
1 ln f (t) dt = —^ I ln tdt = ln I (a, b),
b a b a
1
1
b b 11
t ln f (t) dt = -- t ln tdt =
b — a b — a
aa
1
= - A (a, b) ln I (a2, b2) = ln I/ (a2, b2 )1 A(a,b)
2 L
and
b b
ln f (t) , /" ln t ! b — a , ^ ( 1 , 1 )т -1
"F"1dt = ~Fdt = "¡S" Г'(a 1-1)1
J _ d = I -2dt =— 'n I1 (a-1,6
g
giving that
b
a /fdt = ln [i (a-1,6-1)]-1 •
6 — a 7 t2 L v '
g
Now, if we write the inequality (4) for the function f : [a, 6] C (0, to) ^ ^ (0, to), f (t) = t, we get
( 2a6 \1-A ( 2a6 \A
H (a,6) <V(1 — A) a + (A + 1) 67 V(2 — A) a r A6 J <
< [I (a-1,6-1)]-1 < ^((1 — A^a + A*) ^* < G (a, 6), (32)
where H (a, 6) := g+b is the harmonic mean.
If we use the inequality (6) for f (t) = t, then we have
(L(a,b)-a)b (b-L(a,b))a
(L (a, 6) <) I (a, 6) < 6 (b a) L(a,b) a (b-a)L(a,b) . (33)
If we use the inequality (7) for f (t) = t, t E [a, 6], then we also get
[A (a, 6)] A(g'b) < I (a2, 62) 1 A(g,b) < G (6b, ag0 . (34)
From (8) and (9) for f (t) = t we have
1 < tlw1 <exp (^ l (35)
and
1 < w^ < • (36)
From (10) and (11) we also have
G aa,bb) (b) i(b-a) , x
1 *-V \[, ,, * - (37)
* [I(a2,62)]2A(ab) *Va) ( )
and [ ( )]
[I (a2,b2)] 2Aab) (b) 8(b-a) (38)
1 * [A M)]A<-b) * UJ ■ (38)
Finally, from (13) we obtain
[I (a-1, b-1)]-1 * \JA (a, b) ba^. (39)
Now consider the function f : [a, b] C (0, to) ^ (0, to), f (t) = exp (t). Using the harmonic mean-arithmetic mean inequality we have
f(tx + (7- t) J = exp (tx + (1y- t) y) * exp ((1 - t) x + ty) =
= [exp (x)]1-t [exp (y)]* = [f (x)]1-t [f (y)]*
for any x, y E [a, b] and t E [0,1].
Now, if we use the inequality (4) for the HG-convex function f : [a, b] C C (0, to) ^ (0, to), f (t) = exp (t), then we get, after suitable calculations, that
2 (1 - A) ab 2Aab
H (a b) * (1 - A) a + (A +1) b + (2 - A) a + Ab *
G2 (a, b) 1 ( ab ,„ ., w \ . , ,,
* r, ' * - ^-7t-ry + (1 - A) a + Ab * A (a, b),
" L (a,b) " 2 V(1 - A) a + Ab v y J ~ v J
for any A E [0, 1] .
If we use the inequalities (8) and (9) for the HG-convex function f : [a, b] C (0, to) ^ (0, to), f (t) = exp (t), then, by performing the required calculations, we get
G2 (a,b) 1 A (a, b)
0 < ~ /T/ — H (a, b) < ^ ^Vr?\ (b — a)2 (40)
L (a, b) 4 G2 (a, b)
and
, / G2 (a, b) 1 A (a, b) ,, x2
0 < A(a,b) — T^ < 4GWb-a)2- (41)
From the inequality (13) we also have
G2 M) ^ 1 ,
L (a, b) _ 2
< - (A (a, b) + b^a^^ . (42)
Acknowledgement. The author would like to thank the anonymous referees for valuable comments that have been implemented in the final version of the paper.
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Received April 19, 2017. In revised form, July 11, 2017. Accepted July 11, 2017. Published online August 16, 2017.
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