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Random Stability of an Additive-Quadratic-Quartic Functional Equation
Journal of Inequalities and Applications volume 2010, Article number: 754210 (2010)
Abstract
Using the fixed point method, we prove the generalized Hyers-Ulam stability of the following additive-quadratic-quartic functional equation in complete random normed spaces.
1. Introduction
The stability problem of functional equations originated from a question of Ulam [1] concerning the stability of group homomorphisms. Hyers [2] gave a first affirmative partial answer to the question of Ulam for Banach spaces. Hyers' theorem was generalized by Aoki [3] for additive mappings and by Th. M. Rassias [4] for linear mappings by considering an unbounded Cauchy difference. The paper of Th. M. Rassias [4] has provided a lot of influence in the development of what we call generalized Hyers-Ulam stability or as Hyers-Ulam-Rassias stability of functional equations. A generalization of the Th. M. Rassias theorem was obtained by Gvru
a [5] by replacing the unbounded Cauchy difference by a general control function in the spirit of Th. M. Rassias' approach.
The functional equation

is called a quadratic functional equation. In particular, every solution of the quadratic functional equation is said to be a quadratic mapping. A generalized Hyers-Ulam stability problem for the quadratic functional equation was proved by Skof [6] for mappings , where
is a normed space and
is a Banach space. Cholewa [7] noticed that the theorem of Skof is still true if the relevant domain
is replaced by an Abelian group. Czerwik [8] proved the generalized Hyers-Ulam stability of the quadratic functional equation. The stability problems of several functional equations have been extensively investigated by a number of authors and there are many interesting results concerning this problem (see [4, 9–26]).
In [27], Lee et al. considered the following quartic functional equation

It is easy to show that the function satisfies the functional equation (1.2), which is called a quartic functional equation and every solution of the quartic functional equation is said to be a quartic mapping.
Let be a set. A function
is called a generalized metric on
if
satisfies
(1) if and only if
,
(2) for all
(3) for all
.
We recall a fundamental result in fixed point theory.
Let be a complete generalized metric space and let
be a strictly contractive mapping with Lipschitz constant
. Then for each given element
, either

for all nonnegative integers or there exists a positive integer
such that
(1)
(2)the sequence converges to a fixed point
of
,
(3) is the unique fixed point of
in the set
,
(4) for all
.
In 1996, Isac and Th. M. Rassias [30] were the first to provide applications of stability theory of functional equations for the proof of new fixed point theorems with applications. By using fixed point methods, the stability problems of several functional equations have been extensively investigated by a number of authors (see [31–36]).
2. Preliminaries
In the sequel we adopt the usual terminology, notations and conventions of the theory of random normed spaces, as in [37–41]. Throughout this paper, is the space of all probability distribution functions that is, the space of all mappings
, such that
is left-continuous, non-decreasing on
,
and
.
is a subset of
consising of all functions
for which
, where
denotes the left limit of the function
at the point
, that is,
. The space
is partially ordered by the usual point-wise ordering of functions, that is,
if and only if
for all
in
. The maximal element for
in this order is the distribution function
given by

Definition 2.1 ([40]).
A mapping is a continuous triangular norm (briefly, a
-norm) if
satisfies the following conditions:
(a) is commutative and associative;
(b) is continuous;
(c) for all
;
(d) whenever
and
for all
.
Typical examples of continuous -norms are
,
and
(the
ukasiewicz
-norm).
Recall (see [42, 43]) that if is a
-norm and
is a given sequence of numbers in
,
is defined recurrently by
and
for
.
is defined as
.
It is known ([43]) that for the ukasiewicz
-norm the following implication holds:

Definition 2.2 ([41]).
A Random Normed space (briefly, RN-space) is a triple , where
is a vector space,
is a continuous
-norm, and
is a mapping from
into
such that, the following conditions hold:
(RN1) for all
if and only if
;
(RN2) for all
,
;
(RN3) for all
and
.
Definition 2.3.
Let be a RN-space.
(1)A sequence in
is said to be convergent to
in
if, for every
and
, there exists positive integer
such that
whenever
.
(2)A sequence in
is called Cauchy if, for every
and
, there exists positive integer
such that
whenever
.
(3)A RN-space is said to be complete if and only if every Cauchy sequence in
is convergent to a point in
. A complete RN-space is said to be random Banach space.
Theorem 2.4 ([40]).
If is a RN-space and
is a sequence such that
, then
almost everywhere.
The theory of random normed spaces (RN-spaces) is important as a generalization of deterministic result of linear normed spaces and also in the study of random operator equations. The RN-spaces may also provide us the appropriate tools to study the geometry of nuclear physics and have important application in quantum particle physics. The generalized Hyers-Ulam stability of different functional equations in random normed spaces, RN-spaces and fuzzy normed spaces has been recently studied in, Alsina [44], Mirmostafaee, Mirzavaziri and Moslehian [33, 45–47], Mihe and Radu [38, 39, 48, 49], Mihe
, Saadati and Vaezpour [50, 51], Baktash et al. [52] and Saadati et al. [53].
3. Generalized Hyers-Ulam Stability of the Functional Equation
: An Odd Case
One can easily show that an odd mapping satisfies
if and only if the odd mapping mapping
is an additive mapping, that is,

One can easily show that an even mapping satisfies
if and only if the even mapping
is a quadratic-quartic mapping, that is,

It was shown in [54, Lemma ] that
and
are quartic and quadratic, respectively, and that
.
For a given mapping , we define

for all .
Using the fixed point method, we prove the generalized Hyers-Ulam stability of the functional equation in complete RN-spaces: an odd case.
Theorem 3.1.
Let be a linear space,
be a complete RN-space and
be a mapping from
to
such that, for some
,

Let be an odd mapping satisfying

for all and all
. Then

exists for each and defines a unique additive mapping
such that

for all and all
.
Proof.
Letting in (3.5), we get

for all and all
.
Consider the set

and introduce the generalized metric on :

where, as usual, . It is easy to show that
is complete. (See the proof of Lemma
in [38].)
Now we consider the linear mapping such that

for all and we prove that
is a strictly contractive mapping with the Lipschitz constant
.
Let be given such that
. Then

for all and all
. Hence

for all and all
. So
implies that
. This means that

for all .
It follows from (3.8) that

for all and all
. So

By Theorem 1.1, there exists a mapping satisfying the following:
-
(1)
is a fixed point of
, that is,
(3.17)
for all . The mapping
is a unique fixed point of
in the set

This implies that is a unique mapping satisfying (3.17) such that there exists a
satisfying

for all and all
;
-
(2)
as
. This implies the equality
(3.20)
for all . Since
is odd,
is an odd mapping;
-
(3)
with
, which implies the inequality
(3.21)
from which it follows

This implies that the inequality (3.7) holds.
Now, we have,

for all , all
and all
.
So, we obtain by (3.4)

for all , all
and all
.
Since for all
and all
, by Theorem 2.4, we deduce that

for all and all
. Thus the mapping
is additive, as desired.
Corollary 3.2.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an odd mapping satisfying

for all and all
. Then

exists for each and defines an additive mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 3.1 by taking

for all . Then we can choose
and we get the desired result.
Similarly, we can obtain the following. We will omit the proof.
Theorem 3.3.
Let be a linear space,
be a complete RN-space and
be a mapping from
to
(
is denoted by
)such that, for some
,

Let be an odd mapping satisfying (3.5). Then

exists for each and defines a unique additive mapping
such that

for all and all
.
Corollary 3.4.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an odd mapping satisfying (3.26). Then

exists for each and defines a unique additive mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 3.3 by taking

for all . Then we can choose
and we get the desired result.
4. Generalized Hyers-Ulam Stability of the Functional Equation
: An Even Case
Using the fixed point method, we prove the generalized Hyers-Ulam stability of the functional equation in random Banach spaces: an even case.
Theorem 4.1.
Let be a linear space, let
be a complete RN-space and
be a mapping from
to
(
is denoted by
)such that, for some
,

Let be an even mapping satisfying
and (3.5). Then

exists for each and defines a quartic mapping
such that

for all and all
.
Proof.
Letting in (3.5), we get

for all and all
.
Replacing by
in (3.5), we get

for all and all
.
By (4.4) and (4.5),

for all and all
. Letting
for all
, we get

for all and all
.
Let be the generalized metric space defined in the proof of Theorem 3.1.
Now we consider the linear mapping such that

for all . It is easy to see that
is a strictly contractive self-mapping on
with the Lipschitz constant
.
It follows from (4.7) that

for all and all
. So

By Theorem 1.1, there exists a mapping satisfying the following:
-
(1)
is a fixed point of
, that is,
(4.11)
for all . Since
is even with
,
is an even mapping with
. The mapping
is a unique fixed point of
in the set

This implies that is a unique mapping satisfying (4.11) such that there exists a
satisfying

for all and all
;
-
(2)
as
. This implies the equality
(4.14)
for all ;
-
(3)
for every
, which implies the inequality
(4.15)
This implies that the inequality (4.3) holds.
Proceeding as in the proof of Theorem 3.1, we obtain that the mapping satisfies
.
Now, we have

for every . Since the mapping
is quartic (see [54, Lemma
]), we get that the mapping
is quartic.
Corollary 4.2.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an even mapping satisfying
and (3.26). Then

exists for each and defines a quartic mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 3.1 by taking

for all . Then we can choose
and we get the desired result.
Similarly, we can obtain the following. We will omit the proof.
Theorem 4.3.
Let be a linear space,
be a complete RN-space and
be a mapping from
to
(
is denoted by
)such that, for some
,

Let be an even mapping satisfying
and (3.5). Then

exists for each and defines a quartic mapping
such that

for all and all
.
Corollary 4.4.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an even mapping satisfying
and (3.26). Then

exists for each and defines a quartic mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 3.3 by taking

for all . Then we can choose
and we get the desired result.
Theorem 4.5.
Let be a linear space,
be a complete RN-space and
be a mapping from
to
(
is denoted by
)such that, for some
,

Let be an even mapping satisfying
and (3.5). Then

exists for each and defines a quadratic mapping
such that

for all and all
.
Proof.
Let be the generalized metric space defined in the proof of Theorem 4.1.
Letting for all
in (4.6), we get

for all and all
.
It is easy to see that the linear mapping such that

for all , is a strictly contractive self-mapping with the Lipschitz constant
.
It follows from (4.29) that

for all and all
. So

By Theorem 1.1, there exists a mapping satisfying the following.
-
(1)
is a fixed point of
, that is,
(4.33)
for all . Since
is even with
,
is an even mapping with
. The mapping
is a unique fixed point of
in the set

This implies that is a unique mapping satisfying (4.33) such that there exists a
satisfying

for all and all
;
-
(2)
as
. This implies the equality
(4.36)
for all ;
-
(3)
for each
, which implies the inequality
(4.37)
This implies that the inequality (4.28) holds.
Proceeding as in the proof of Theorem 4.1, we obtain that the mapping satisfies
.
Now, we have

for every . Since the mapping
is quadratic (see [54, Lemma
]), we get that the mapping
is quadratic.
Corollary 4.6.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an even mapping satisfying
and (3.26). Then

exists for each and defines a quadratic mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 4.5 by taking

for all . Then we can choose
and we get the desired result.
Similarly, we can obtain the following. We will omit the proof.
Theorem 4.7.
Let be a linear space,
be a complete RN-space and
be a mapping from
to
(
is denoted by
) such that, for some
,

Let be an even mapping satisfying
and (3.5). Then

exists for each and defines a quadratic mapping
such that

for all and all
.
Corollary 4.8.
Let and let
be a real number with
. Let
be a normed vector space with norm
. Let
be an even mapping satisfying
and (3.26). Then

exists for each and defines a quadratic mapping
such that

for all and all
.
Proof.
The proof follows from Theorem 4.7 by taking

for all . Then we can choose
and we get the desired result.
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Acknowledgments
The authors would like to thank referees for giving useful suggestions for the improvement of this paper. The first author is supported by Islamic Azad University-Ayatollah Amoli Branch, Amol, Iran. The second author was supported by the Korea Research Foundation Grant funded by the Korean Government (KRF-2008-313-C00050) and the third author was supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (NRF-2009-0070788). The fourth author is supported by Università degli Studi di Palermo, R.S. ex 60%.
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Mohamadi, M., Cho, Y., Park, C. et al. Random Stability of an Additive-Quadratic-Quartic Functional Equation. J Inequal Appl 2010, 754210 (2010). https://doi.org/10.1155/2010/754210
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DOI: https://doi.org/10.1155/2010/754210
Keywords
- Functional Equation
- Linear Space
- Quadratic Mapping
- Unique Fixed Point
- Normed Vector Space