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Fuzzy stability of functional inequalities in matrix fuzzy normed spaces

Abstract

Using the fixed point method, we prove the Hyers-Ulam stability of additive functional inequalities in matrix fuzzy normed spaces.

MSC:47L25, 47H10, 46S40, 39B82, 46L07, 39B52, 26E50.

1 Introduction and preliminaries

Katsaras [1] defined a fuzzy norm on a vector space to construct a fuzzy vector topological structure on the space. Some mathematicians have defined fuzzy norms on a vector space from various points of view [24]. In particular, Bag and Samanta [5], following Cheng and Mordeson [6], gave an idea of a fuzzy norm in such a manner that the corresponding fuzzy metric is of Kramosil and Michalek type [7]. They established a decomposition theorem of a fuzzy norm into a family of crisp norms and investigated some properties of fuzzy normed spaces [8].

We use the definition of fuzzy normed spaces given in [5, 9, 10] to investigate a fuzzy version of the Hyers-Ulam stability for the Cauchy additive functional inequality and for the Cauchy-Jensen additive functional inequality in the fuzzy normed vector space setting.

Definition 1.1 [5, 911]

Let X be a real vector space. A function N:X×R[0,1] is called a fuzzy norm on X if for all x,yX and all s,tR,

(N1) N(x,t)=0 for t0;

(N2) x=0 if and only if N(x,t)=1 for all t>0;

(N3) N(cx,t)=N(x, t | c | ) if c0;

(N4) N(x+y,s+t)min{N(x,s),N(y,t)};

(N5) N(x,) is a non-decreasing function of and lim t N(x,t)=1;

(N6) for x0, N(x,) is continuous on .

The pair (X,N) is called a fuzzy normed vector space.

The properties of fuzzy normed vector spaces and examples of fuzzy norms are given in [10, 11].

Definition 1.2 [5, 911]

Let (X,N) be a fuzzy normed vector space. A sequence { x n } in X is said to be convergent or converge if there exists an xX such that lim n N( x n x,t)=1 for all t>0. In this case, x is called the limit of the sequence { x n } and we denote it by N- lim n x n =x.

Definition 1.3 [5, 9, 10]

Let (X,N) be a fuzzy normed vector space. A sequence { x n } in X is called Cauchy if for each ε>0 and each t>0 there exists an n 0 N such that for all n n 0 and all p>0, we have N( x n + p x n ,t)>1ε.

It is well known that every convergent sequence in a fuzzy normed vector space is Cauchy. If each Cauchy sequence is convergent, then the fuzzy norm is said to be complete and the fuzzy normed vector space is called a fuzzy Banach space.

We say that a mapping f:XY between fuzzy normed vector spaces X and Y is continuous at a point x 0 X if for each sequence { x n } converging to x 0 in X, the sequence {f( x n )} converges to f( x 0 ). If f:XY is continuous at each xX, then f:XY is said to be continuous on X (see [8]).

We will use the following notations:

M n (X) is the set of all n×n-matrices in X;

e j M 1 , n (C) is that j th component is 1 and the other components are zero;

E i j M n (C) is that (i,j)-component is 1 and the other components are zero;

E i j x M n (X) is that (i,j)-component is x and the other components are zero.

For x M n (X), y M k (X),

xy=( x 0 0 y ).

Note that (X,{ n }) is a matrix normed space if and only if ( M n (X), n ) is a normed space for each positive integer n and A x B k AB x n holds for A M k , n (C), x=( x i j ) M n (X) and B M n , k (C), and that (X,{ n }) is a matrix Banach space if and only if X is a Banach space and (X,{ n }) is a matrix normed space.

A matrix normed space (X,{ n }) is called an L -matrix normed space if x y n + k =max{ x n , y k } holds for all x M n (X) and all y M k (X).

Let E, F be vector spaces. For a given mapping h:EF and a given positive integer n, define h n : M n (E) M n (F) by

h n ( [ x i j ] ) = [ h ( x i j ) ]

for all [ x i j ] M n (E).

We introduce the concept of a matrix fuzzy normed space.

Definition 1.4 Let (X,N) be a fuzzy normed space.

  1. (1)

    (X,{ N n }) is called a matrix fuzzy normed space if for each positive integer n, ( M n (X), N n ) is a fuzzy normed space and N k (AxB,t) N n (x, t A B ) for all t>0, A M k , n (R), x=[ x i j ] M n (X) and B M n , k (R) with AB0.

  2. (2)

    (X,{ N n }) is called a matrix fuzzy Banach space if (X,N) is a fuzzy Banach space and (X,{ N n }) is a matrix fuzzy normed space.

Example 1.5 Let (X,{ n }) be a matrix normed space. Let N n (x,t):= t t + x n for all t>0 and x=[ x i j ] M n (X). Then

N k (AxB,t)= t t + A x B k t t + A x n B = t A B t A B + x n

for all t>0, A M k , n (R), x=[ x i j ] M n (X) and B M n , k (R) with AB0. So, (X,{ N n }) is a matrix fuzzy normed space.

The abstract characterization given for linear spaces of bounded Hilbert space operators in terms of matricially normed spaces [12] implies that quotients, mapping spaces, and various tensor products of operator spaces may again be regarded as operator spaces. Owing in part to this result, the theory of operator spaces is having an increasingly significant effect on operator algebra theory (see [13]).

The proof given in [12] appealed to the theory of ordered operator spaces [14]. Effros and Ruan [15] showed that one can give a purely metric proof of this important theorem by using a technique of Pisier [16] and Haagerup [17] (as modified in [18]).

The stability problem of functional equations originated from a question of Ulam [19] concerning the stability of group homomorphisms. Hyers [20] gave the first affirmative partial answer to the question of Ulam for Banach spaces. Hyers’ theorem was generalized by Aoki [21] for additive mappings and by Rassias [22] for linear mappings by considering an unbounded Cauchy difference. A generalization of the Rassias theorem was obtained by Găvruta [23] by replacing the unbounded Cauchy difference by a general control function in the spirit of Rassias’ approach.

In [24], Gilányi showed that if f satisfies the functional inequality

2 f ( x ) + 2 f ( y ) f ( x y 1 ) f ( x y ) ,
(1.1)

then f satisfies the Jordan-von Neumann functional equation

2f(x)+2f(y)=f(xy)+f ( x y 1 ) .

See also [25]. Gilányi [26] and Fechner [27] proved the Hyers-Ulam stability of the functional inequality (1.1).

Park et al. [28] proved the Hyers-Ulam stability of the following functional inequalities:

f ( x ) + f ( y ) + f ( z ) 2 f ( x + y + z 2 ) , f ( x ) + f ( y ) + f ( z ) f ( x + y + z ) ,
(1.2)
f ( x ) + f ( y ) + 2 f ( z ) 2 f ( x + y 2 + z ) .
(1.3)

Let X be a set. A function d:X×X[0,] is called a generalized metric on X if d satisfies

  1. (1)

    d(x,y)=0 if and only if x=y;

  2. (2)

    d(x,y)=d(y,x) for all x,yX;

  3. (3)

    d(x,z)d(x,y)+d(y,z) for all x,y,zX.

We recall a fundamental result in fixed point theory.

Theorem 1.6 [29, 30]

Let (X,d) be a complete generalized metric space and let J:XX be a strictly contractive mapping with a Lipschitz constant α<1. Then, for each given element xX, either

d ( J n x , J n + 1 x ) =

for all nonnegative integers n or there exists a positive integer n 0 such that

  1. (1)

    d( J n x, J n + 1 x)<, n n 0 ;

  2. (2)

    the sequence { J n x} converges to a fixed point y of J;

  3. (3)

    y is the unique fixed point of J in the set Y={yXd( J n 0 x,y)<};

  4. (4)

    d(y, y ) 1 1 α d(y,Jy) for all yY.

In 1996, Isac and Rassias [31] 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 [3238]).

Throughout this paper, let (X, n ) be a matrix normed space, (Y, n ) be a matrix Banach space and let n be a fixed positive integer. Let (X, N n ) be a matrix fuzzy normed space and let (Y, N n ) be a matrix fuzzy Banach space.

In Section 2, we prove the Hyers-Ulam stability of the Cauchy additive functional inequality (1.2) in fuzzy normed spaces by using the fixed point method.

In Section 3, we prove the Hyers-Ulam stability of the Cauchy additive functional equation in matrix fuzzy normed spaces by using the fixed point method.

In Section 4, we prove the Hyers-Ulam stability of the Cauchy-Jensen additive functional inequality (1.3) in fuzzy normed spaces by using the fixed point method.

In Section 5, we prove the Hyers-Ulam stability of the Cauchy additive functional inequality (1.2) in matrix normed spaces by using the direct method and by using the fixed point method.

2 Hyers-Ulam stability of the Cauchy functional inequality in fuzzy normed spaces

We need the following lemma to prove the main results.

Lemma 2.1 [16, 39]

Let (Y,N) be a fuzzy normed vector space. Let f:XY be a mapping such that

N ( f ( x ) + f ( y ) + 2 f ( z ) , t ) N ( 2 f ( x + y 2 + z ) , 2 t 3 )

for all x,y,zX and all t>0. Then f is Cauchy additive, i.e., f(x+y)=f(x)+f(y) for all x,yX.

In this section, using the fixed point method, we prove the Hyers-Ulam stability of the Cauchy additive functional inequality (1.2) in fuzzy Banach spaces.

Theorem 2.2 Let φ: X 3 [0,) be a function such that there exists an L<1 with

φ(x,y,z) L 2 φ(2x,2y,2z)

for all x,y,zX. Let f:XY be an odd mapping satisfying

N ( f ( x ) + f ( y ) + f ( z ) , t ) min { N ( f ( x + y + z ) , t 2 ) , t t + φ ( x , y , z ) }
(2.1)

for all x,y,zX and all t>0. Then A(x):=N- lim n 2 n f( x 2 n ) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 L ) t ( 2 2 L ) t + L φ ( x , x , 2 x )
(2.2)

for all xX and all t>0.

Proof Since f is odd, f(0)=0. So, N(f(0), t 2 )=1. Letting y=x and replacing z by 2x in (2.1), we get

N ( f ( 2 x ) 2 f ( x ) , t ) t t + φ ( x , x , 2 x )
(2.3)

for all xX.

Consider the set

S:={g:XY}

and introduce the generalized metric on S:

d(g,h)=inf { μ R + : N ( g ( x ) h ( x ) , μ t ) t t + φ ( x , x , 2 x ) , x X , t > 0 } ,

where, as usual, infϕ=+. It is easy to show that (S,d) is complete. (See the proof of [[40], Lemma 2.1].)

Now we consider the linear mapping J:SS such that

Jg(x):=2g ( x 2 )

for all xX.

Let g,hS be given such that d(g,h)=ε. Then

N ( g ( x ) h ( x ) , ε t ) t t + φ ( x , x , 2 x )

for all xX and all t>0. Hence

N ( J g ( x ) J h ( x ) , L ε t ) = N ( 2 g ( x 2 ) 2 h ( x 2 ) , L ε t ) = N ( g ( x 2 ) h ( x 2 ) , L 2 ε t ) L t 2 L t 2 + φ ( x 2 , x 2 , x ) L t 2 L t 2 + L 2 φ ( x , x , 2 x ) = t t + φ ( x , x , 2 x )

for all xX and all t>0. So, d(g,h)=ε implies that d(Jg,Jh)Lε. This means that

d(Jg,Jh)Ld(g,h)

for all g,hS.

It follows from (2.3) that

N ( f ( x ) 2 f ( x 2 ) , L 2 t ) t t + φ ( x , x , 2 x )

for all xX and all t>0. So, d(f,Jf) L 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A ( x 2 ) = 1 2 A(x)
    (2.4)

for all xX. Since f:XY is odd, A:XY is an odd mapping. The mapping A is a unique fixed point of J in the set

M= { g S : d ( f , g ) < } .

This implies that A is a unique mapping satisfying (2.4) such that there exists a μ(0,) satisfying

N ( f ( x ) A ( x ) , μ t ) t t + φ ( x , x , 2 x )

for all xX;

  1. (2)

    d( J n f,A)0 as n. This implies the equality

    N- lim n 2 n f ( x 2 n ) =A(x)

for all xX;

  1. (3)

    d(f,A) 1 1 L d(f,Jf), which implies the inequality

    d(f,A) L 2 2 L .

This implies that the inequality (2.2) holds.

By (2.1),

N ( 2 n ( f ( x 2 n ) + f ( y 2 n ) + f ( z 2 n ) ) , 2 n t ) min { N ( 2 n f ( x + y + z 2 n ) , 2 n 1 t ) , t t + φ ( x 2 n , y 2 n , z 2 n ) }

for all x,y,zX, all t>0, and all nN. So,

N ( 2 n ( f ( x 2 n ) + f ( y 2 n ) + f ( z 2 n ) ) , t ) min { N ( 2 n f ( x + y + z 2 n ) , t 2 ) , t 2 n t 2 n + L n 2 n φ ( x , y , z ) }

for all x,y,zX, all t>0, and all nN. Since lim n t 2 n t 2 n + L n 2 n φ ( x , y , z ) =1 for all x,y,zX and all t>0,

N ( A ( x ) + A ( y ) + A ( z ) , t ) N ( A ( x + y + z ) , t 2 )

for all x,y,zX and all t>0. By [[41], Lemma 2.1], the mapping A:XY is a Cauchy additive, as desired. □

Corollary 2.3 Let θ0 and let p be a real number with p>1. Let X be a normed vector space with the norm . Let f:XY be an odd mapping satisfying

N ( f ( x ) + f ( y ) + f ( z ) , t ) min { N ( f ( x + y + z ) , t 2 ) , t t + θ ( x p + y p + z p ) }
(2.5)

for all x,y,zX and all t>0. Then A(x):=N- lim n 2 n f( x 2 n ) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 p 2 ) t ( 2 p 2 ) t + ( 2 + 2 p ) θ x p

for all xX and all t>0.

Proof The proof follows from Theorem 2.2 by taking

φ(x,y):=θ ( x p + y p + z p )

for all x,y,zX. Then we can choose L= 2 1 p , and we get the desired result. □

Theorem 2.4 Let φ: X 3 [0,) be a function such that there exists an L<1 with

φ(x,y,z)2Lφ ( x 2 , y 2 , z 2 )

for all x,y,zX. Let f:XY be an odd mapping satisfying (2.1). Then A(x):=N- lim n 1 2 n f( 2 n x) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 L ) t ( 2 2 L ) t + φ ( x , x , 2 x )
(2.6)

for all xX and all t>0.

Proof Let (S,d) be the generalized metric space defined in the proof of Theorem 2.2.

Consider the linear mapping J:SS such that

Jg(x):= 1 2 g(2x)

for all xX.

Let g,hS be given such that d(g,h)=ε. Then

N ( g ( x ) h ( x ) , ε t ) t t + φ ( x , x , 2 x )

for all xX and all t>0. Hence

N ( J g ( x ) J h ( x ) , L ε t ) = N ( 1 2 g ( 2 x ) 1 2 h ( 2 x ) , L ε t ) = N ( g ( 2 x ) h ( 2 x ) , 2 L ε t ) 2 L t 2 L t + φ ( 2 x , 2 x , 4 x ) 2 L t 2 L t + 2 L φ ( x , x , 2 x ) = t t + φ ( x , x , 2 x )

for all xX and all t>0. So, d(g,h)=ε implies that d(Jg,Jh)Lε. This means that

d(Jg,Jh)Ld(g,h)

for all g,hS.

It follows from (2.3) that

N ( f ( x ) 1 2 f ( 2 x ) , 1 2 t ) t t + φ ( x , x , 2 x )

for all xX and all t>0. So, d(f,Jf) 1 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A(2x)=2A(x)
    (2.7)

for all xX. Since f:XY is odd, A:XY is an odd mapping. The mapping A is a unique fixed point of J in the set

M= { g S : d ( f , g ) < } .

This implies that A is a unique mapping satisfying (2.7) such that there exists a μ(0,) satisfying

N ( f ( x ) A ( x ) , μ t ) t t + φ ( x , x , 2 x )

for all xX;

  1. (2)

    d( J n f,A)0 as n. This implies the equality

    N- lim n 1 2 n f ( 2 n x ) =A(x)

for all xX;

  1. (3)

    d(f,A) 1 1 L d(f,Jf), which implies the inequality

    d(f,A) 1 2 2 L .

This implies that the inequality (2.6) holds.

The rest of the proof is similar to the proof of Theorem 2.2. □

Corollary 2.5 Let θ0 and let p be a real number with 0<p<1. Let X be a normed vector space with the norm . Let f:XY be an odd mapping satisfying (2.5). Then A(x):=N- lim n 1 2 n f( 2 n x) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 p ) t ( 2 2 p ) t + ( 2 + 2 p ) θ x p

for all xX and all t>0.

Proof The proof follows from Theorem 2.4 by taking

φ(x,y):=θ ( x p + y p + z p )

for all x,y,zX. Then we can choose L= 2 p 1 , and we get the desired result. □

3 Hyers-Ulam stability of the Cauchy additive functional equation in matrix fuzzy normed spaces

Using a fixed point method, we prove the Hyers-Ulam stability of the Cauchy additive functional equation in matrix fuzzy normed spaces.

We will use the following notations:

M n (X) is the set of all n×n-matrices in X;

e j M 1 , n (R) is that j th component is 1 and the other components are zero;

E i j M n (R) is that (i,j)-component is 1 and the other components are zero;

E i j x M n (X) is that (i,j)-component is x and the other components are zero.

Lemma 3.1 Let (X,{ N n }) be a matrix fuzzy normed space.

  1. (1)

    N n ( E k l x,t)=N(x,t) for all t>0 and xX.

  2. (2)

    For all [ x i j ] M n (X) and t= i , j = 1 n t i j ,

    N ( x k l , t ) N n ( [ x i j ] , t ) min { N ( x i j , t i j ) : i , j = 1 , 2 , , n } , N ( x k l , t ) N n ( [ x i j ] , t ) min { N ( x i j , t n 2 ) : i , j = 1 , 2 , , n } .
  3. (3)

    lim n x n =x if and only if lim n x i j n = x i j for x n =[ x i j n ], x=[ x i j ] M k (X).

Proof (1) Since E k l x= e k x e l and e k = e l =1, N n ( E k l x,t)N(x,t). Since e k ( E k l x) e l =x, N n ( E k l x,t)N(x,t). So, N( E k l x,t)=N(x,t).

  1. (2)

    N( x k l ,t)=N( e k [ x i j ] e l ,t) N n ([ x i j ], t e k e l )= N n ([ x i j ],t).

    N n ( [ x i j ] , t ) = N n ( i , j = 1 n E i j x i j , t ) min { N n ( E i j x i j , t i j ) : i , j = 1 , 2 , , n } = min { N ( x i j , t i j ) : i , j = 1 , 2 , , n } ,

where t= i , j = 1 n t i j . So, N n ([ x i j ],t)min{N( x i j , t n 2 ):i,j=1,2,,n}.

  1. (3)

    By N( x k l ,t) N n ([ x i j ],t)min{N( x i j , t n 2 ):i,j=1,2,,n}, we obtain the result. □

For a mapping f:XY, define Df: X 2 Y and D f n : M n ( X 2 ) M n (Y) by

D f ( a , b ) = f ( a + b ) f ( a ) f ( b ) , D f n ( [ x i j ] , [ y i j ] ) : = f n ( [ x i j + y i j ] ) f n ( [ x i j ] ) f n ( [ y i j ] )

for all a,bX and all x=[ x i j ],y=[ y i j ] M n (X).

Theorem 3.2 Let φ: X 2 [0,) be a function such that there exists an α<1 with

φ(a,b) α 2 φ(2a,2b)
(3.1)

for all a,bX. Let f:XY be a mapping satisfying

N n ( D f n ( [ x i j ] , [ y i j ] ) , t ) t t + i , j = 1 n φ ( x i j , y i j )
(3.2)

for all t>0 and x=[ x i j ],y=[ y i j ] M n (X). Then A(a):=N- lim l 2 l f( a 2 l ) exists for each aX and defines an additive mapping A:XY such that

N ( f n ( [ x i j ] ) A n ( [ x i j ] ) , t ) 2 ( 1 α ) t 2 ( 1 α ) t + n 2 α i , j = 1 n φ ( x i j , x i j )
(3.3)

for all t>0 and x=[ x i j ] M n (X).

Proof Let n=1. Then (3.2) is equivalent to

N ( f ( a + b ) f ( a ) f ( b ) , t ) t t + φ ( a , b )
(3.4)

for all t>0 and a,bX.

Letting b=a in (3.4), we get

N ( f ( 2 a ) 2 f ( a ) , t ) t t + φ ( a , a )
(3.5)

and so

N ( f ( a ) 2 f ( a 2 ) , t ) t t + φ ( a 2 , a 2 ) t t + α 2 φ ( a , a )
(3.6)

for all t>0 and aX.

Consider the set

S:={g:XY}

and introduce the generalized metric on S:

d(g,h)=inf { μ R + : N ( g ( a ) h ( a ) , μ t ) t t + φ ( a , a ) , a X , t > 0 } ,

where, as usual, infϕ=+. It is easy to show that (S,d) is complete (see the proof of [[40], Lemma 2.1]).

Now we consider the linear mapping J:SS such that

Jg(a):=2g ( a 2 )

for all aX.

Let g,hS be given such that d(g,h)=ε. Then

N ( g ( a ) h ( a ) , ε t ) t t + φ ( a , a )

for all aX and t>0. Hence

N ( J g ( a ) J h ( a ) , α ε t ) = N ( 2 g ( a 2 ) 2 h ( a 2 ) , α ε t ) = N ( g ( a 2 ) h ( a 2 ) , α 2 ε t ) α t 2 α t 2 + φ ( a 2 , a 2 ) α t 2 α t 2 + α 2 φ ( a , a ) = t t + φ ( a , a )

for all aX and t>0. So, d(g,h)=ε implies that d(Jg,Jh)αε. This means that

d(Jg,Jh)αd(g,h)

for all g,hS.

It follows from (3.6) that d(f,Jf) α 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A ( a 2 ) = 1 2 A(a)

for all aX. The mapping A is a unique fixed point of J in the set

M= { g S : d ( f , g ) < } .
  1. (2)

    d( J l f,A)0 as l. This implies the equality

    N- lim l 2 l f ( a 2 l ) =A(a)

for all aX.

  1. (3)

    d(f,A) 1 1 α d(f,Jf), which implies the inequality

    d(f,A) α 2 2 α .
    (3.7)

By (3.4),

N ( 2 l f ( a + b 2 l ) 2 l f ( a 2 l ) 2 l f ( b 2 l ) , 2 l t ) t t + φ ( a 2 l , b 2 l )

for all a,bX and t>0. So,

N ( 2 l f ( a + b 2 l ) 2 l f ( a 2 l ) 2 l f ( b 2 l ) , t ) t 2 l t 2 l + α l 2 l φ ( a , b )

for all a,bX and t>0. Since lim l t 2 l t 2 l + α l 2 l φ ( a , b ) =1 for all a,bX and t>0,

N ( A ( a + b ) A ( a ) A ( b ) , t ) =1

for all a,bX and t>0. Thus A(a+b)A(a)A(b)=0. So, the mapping A:XY is additive.

By Lemma 3.1 and (3.7),

N n ( f n ( [ x i j ] ) A n ( [ x i j ] ) , t ) min { N ( f ( x i j ) A ( x i j ) , t n 2 ) : i , j = 1 , 2 , , n } min { 2 ( 1 α ) t 2 ( 1 α ) t + n 2 α φ ( x i j , x i j ) : i , j = 1 , 2 , , n } 2 ( 1 α ) t 2 ( 1 α ) t + n 2 α i , j = 1 n φ ( x i j , x i j )

for all x=[ x i j ] M n (X). Thus A:XY is a unique additive mapping satisfying (3.3), as desired. □

Corollary 3.3 Let r, θ be positive real numbers with r<1. Let f:XY be a mapping satisfying

N n ( D f n ( [ x i j ] , [ y i j ] ) , t ) t t + i , j = 1 n θ ( x i j r + y i j r )
(3.8)

for all t>0 and x=[ x i j ],y=[ y i j ] M n (X). Then A(a):=N- lim l 2 l f( a 2 l ) exists for each aX and defines an additive mapping A:XY such that

N ( f n ( [ x i j ] ) A n ( [ x i j ] ) , t ) ( 2 2 r ) t ( 2 2 r ) t + n 2 2 r i , j = 1 n θ x i j r

for all t>0 and x=[ x i j ] M n (X).

Proof The proof follows from Theorem 3.2 by taking φ(a,b)=θ( a r + b r ) for all a,bX. Then we can choose α= 2 r 1 , and we get the desired result. □

Theorem 3.4 Let f:XY be a mapping satisfying (3.2) for which there exists a function φ: X 2 [0,) such that there exists an α<1 with

φ(a,b)2αφ ( a 2 , b 2 )

for all a,bX. Then A(a):=N- lim l 1 2 l f( 2 l a) exists for each aX and defines an additive mapping A:XY such that

N ( f n ( [ x i j ] ) A n ( [ x i j ] ) , t ) 2 ( 1 α ) t 2 ( 1 α ) t + n 2 i , j = 1 n φ ( x i j , x i j )

for all t>0 and x=[ x i j ] M n (X).

Proof Let (S,d) be the generalized metric space defined in the proof of Theorem 3.2.

Now we consider the linear mapping J:SS such that

Jg(a):=2g ( a 2 )

for all aX.

It follows from (3.5) that d(f,Jf) 1 2 . So,

d(f,A) 1 2 2 α .

The rest of the proof is similar to the proof of Theorem 3.2. □

Corollary 3.5 Let r, θ be positive real numbers with r>1. Let f:XY be a mapping satisfying (3.8). Then A(a):=N- lim l 2 l f( a 2 l ) exists for each aX and defines an additive mapping A:XY such that

N ( f n ( [ x i j ] ) A n ( [ x i j ] ) , t ) ( 2 r 2 ) t ( 2 r 2 ) t + n 2 2 r i , j = 1 n θ x i j r

for all t>0 and x=[ x i j ] M n (X).

Proof The proof follows from Theorem 3.4 by taking φ(a,b)=θ( a r + b r ) for all a,bX. Then we can choose α= 2 1 r , and we get the desired result. □

4 Fuzzy stability of the Cauchy-Jensen additive functional inequality (1.3) in fuzzy normed spaces

In this section, using the fixed point method, we prove the generalized Hyers-Ulam stability of the Cauchy-Jensen additive functional inequality (1.3) in fuzzy Banach spaces.

Theorem 4.1 Let φ: X 3 [0,) be a function such that there exists an L<1 with

φ(x,y,z) L 2 φ(2x,2y,2z)

for all x,y,zX. Let f:XY be an odd mapping satisfying

N ( f ( x ) + f ( y ) + f ( 2 z ) , t ) min { N ( 2 f ( x + y 2 + z ) , 2 t 3 ) , t t + φ ( x , y , z ) }
(4.1)

for all x,y,zX and all t>0. Then A(x):=N- lim n 2 n f( x 2 n ) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 L ) t ( 2 2 L ) t + L φ ( x , x , x )
(4.2)

for all xX and all t>0.

Proof Letting y=x=z in (4.1), we get

N ( f ( 2 x ) 2 f ( x ) , t ) t t + φ ( x , x , x )
(4.3)

for all xX.

Consider the set

S:={g:XY}

and introduce the generalized metric on S:

d(g,h)=inf { μ R + : N ( g ( x ) h ( x ) , μ t ) t t + φ ( x , x , x ) , x X , t > 0 } ,

where, as usual, infϕ=+. It is easy to show that (S,d) is complete. (See the proof of [[40], Lemma 2.1].)

Now we consider the linear mapping J:SS such that

Jg(x):=2g ( x 2 )

for all xX.

Let g,hS be given such that d(g,h)=ε. Then

N ( g ( x ) h ( x ) , ε t ) t t + φ ( x , x , x )

for all xX and all t>0. Hence

N ( J g ( x ) J h ( x ) , L ε t ) = N ( 2 g ( x 2 ) 2 h ( x 2 ) , L ε t ) = N ( g ( x 2 ) h ( x 2 ) , L 2 ε t ) L t 2 L t 2 + φ ( x 2 , x 2 , x 2 ) L t 2 L t 2 + L 2 φ ( x , x , x ) = t t + φ ( x , x , x )

for all xX and all t>0. So, d(g,h)=ε implies that d(Jg,Jh)Lε. This means that

d(Jg,Jh)Ld(g,h)

for all g,hS.

It follows from (4.3) that

N ( f ( x ) 2 f ( x 2 ) , L 2 t ) t t + φ ( x , x , x )

for all xX and all t>0. So, d(f,Jf) L 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A ( x 2 ) = 1 2 A(x)
    (4.4)

for all xX. Since f:XY is odd, A:XY is an odd mapping. The mapping A is a unique fixed point of J in the set

M= { g S : d ( f , g ) < } .

This implies that A is a unique mapping satisfying (4.4) such that there exists a μ(0,) satisfying

N ( f ( x ) A ( x ) , μ t ) t t + φ ( x , x , x )

for all xX;

  1. (2)

    d( J n f,A)0 as n. This implies the equality

    N- lim n 2 n f ( x 2 n ) =A(x)

for all xX;

  1. (3)

    d(f,A) 1 1 L d(f,Jf), which implies the inequality

    d(f,A) L 2 2 L .

This implies that the inequality (4.2) holds.

The rest of proof is similar to the proof of Theorem 2.2. □

Corollary 4.2 Let θ0 and let p be a real number with p>1. Let X be a normed vector space with the norm . Let f:XY be an odd mapping satisfying

N ( f ( x ) + f ( y ) + f ( 2 z ) , t ) min { N ( f ( x + y 2 + z ) , 2 t 3 ) , t t + θ ( x p + y p + z p ) }
(4.5)

for all x,y,zX and all t>0. Then A(x):=N- lim n 2 n f( x 2 n ) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 p 2 ) t ( 2 p 2 ) t + 3 θ x p

for all xX and all t>0.

Proof The proof follows from Theorem 4.1 by taking

φ(x,y):=θ ( x p + y p + z p )

for all x,y,zX. Then we can choose L= 2 1 p , and we get the desired result. □

Theorem 4.3 Let φ: X 3 [0,) be a function such that there exists an L<1 with

φ(x,y,z)2Lφ ( x 2 , y 2 , z 2 )

for all x,y,zX. Let f:XY be an odd mapping satisfying (4.1). Then A(x):=N- lim n 1 2 n f( 2 n x) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 L ) t ( 2 2 L ) t + φ ( x , x , x )
(4.6)

for all xX and all t>0.

Proof Let (S,d) be the generalized metric space defined in the proof of Theorem 4.1.

Consider the linear mapping J:SS such that

Jg(x):= 1 2 g(2x)

for all xX.

Let g,hS be given such that d(g,h)=ε. Then

N ( g ( x ) h ( x ) , ε t ) t t + φ ( x , x , x )

for all xX and all t>0. Hence

N ( J g ( x ) J h ( x ) , L ε t ) = N ( 1 2 g ( 2 x ) 1 2 h ( 2 x ) , L ε t ) = N ( g ( 2 x ) h ( 2 x ) , 2 L ε t ) 2 L t 2 L t + φ ( 2 x , 2 x , 2 x ) 2 L t 2 L t + 2 L φ ( x , x , x ) = t t + φ ( x , x , x )

for all xX and all t>0. So, d(g,h)=ε implies that d(Jg,Jh)Lε. This means that

d(Jg,Jh)Ld(g,h)

for all g,hS.

It follows from (4.3) that

N ( f ( x ) 1 2 f ( 2 x ) , 1 2 t ) t t + φ ( x , x , x )

for all xX and all t>0. So, d(f,Jf) 1 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A(2x)=2A(x)
    (4.7)

for all xX. Since f:XY is odd, A:XY is an odd mapping. The mapping A is a unique fixed point of J in the set

M= { g S : d ( f , g ) < } .

This implies that A is a unique mapping satisfying (4.7) such that there exists a μ(0,) satisfying

N ( f ( x ) A ( x ) , μ t ) t t + φ ( x , x , x )

for all xX;

  1. (2)

    d( J n f,A)0 as n. This implies the equality

    N- lim n 1 2 n f ( 2 n x ) =A(x)

for all xX;

  1. (3)

    d(f,A) 1 1 L d(f,Jf), which implies the inequality

    d(f,A) 1 2 2 L .

This implies that the inequality (4.6) holds.

The rest of the proof is similar to the proof of Theorem 2.2. □

Corollary 4.4 Let θ0 and let p be a real number with 0<p<1. Let X be a normed vector space with the norm . Let f:XY be an odd mapping satisfying (4.5). Then A(x):=N- lim n 1 2 n f( 2 n x) exists for each xX and defines an additive mapping A:XY such that

N ( f ( x ) A ( x ) , t ) ( 2 2 p ) t ( 2 2 p ) t + 3 θ x p

for all xX and all t>0.

Proof The proof follows from Theorem 4.3 by taking

φ(x,y):=θ ( x p + y p + z p )

for all x,y,zX. Then we can choose L= 2 p 1 , and we get the desired result. □

5 Hyers-Ulam stability of the additive functional inequality (1.2) in matrix normed spaces

In this section, we prove the Hyers-Ulam stability of the additive functional inequality (1.2) in matrix normed spaces by using the direct method and by using the fixed point method.

Lemma 5.1 Let (X,{ n }) be a matrix normed space.

  1. (1)

    E k l x n =x for xX;

  2. (2)

    x k l [ x i j ] n i , j = 1 n x i j for [ x i j ] M n (X);

  3. (3)

    lim n x n =x if and only if lim n x n i j = x i j for x n =[ x n i j ],x=[ x i j ] M k (X).

Proof (1) Since E k l x= e k x e l and e k = e l =1, E k l x n x. Since e k ( E k l x) e l =x, x E k l x n . So, E k l x n =x.

  1. (2)

    Since e k x e l = x k l and e k = e l =1, x k l [ x i j ] n .

Since [ x i j ]= i , j = 1 n E i j x i j ,

[ x i j ] n = i , j = 1 n E i j x i j n i , j = 1 n E i j x i j n = i , j = 1 n x i j .
  1. (3)

    By (2), we have

    x n k l x k l [ x n i j x i j ] n = [ x n i j ] [ x i j ] n i , j = 1 n x n i j x i j .

So, we get the result. □

We need the following result.

Lemma 5.2 [[28], Proposition 2.2]

Let f:XY be a mapping such that

f ( a ) + f ( b ) + f ( c ) f ( a + b + c )

for all a,b,cX. Then f:XY is additive.

Theorem 5.3 Let f:XY be a mapping and let ϕ: X 3 [0,) be a function such that

Φ ( a , b , c ) : = 1 2 l = 0 1 2 l ϕ ( 2 l a , 2 l b , 2 l c ) < + ,
(5.1)
f n ( [ x i j ] ) + f n ( [ y i j ] ) + f n ( [ z i j ] ) n f n ( [ x i j ] + [ y i j ] + [ z i j ] ) n + i , j = 1 n ϕ ( x i j , y i j , z i j )
(5.2)

for all a,b,cX and all x=[ x i j ],y=[ y i j ],z=[ z i j ] M n (X). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n Φ( x i j , x i j ,2 x i j )
(5.3)

for all x=[ x i j ] M n (X).

Proof When n=1, (5.2) is equivalent to

f ( a ) + f ( b ) + f ( c ) f ( a + b + c ) +ϕ(a,b,c)

for all a,b,cX. By the same reasoning as in the proof of [[28], Theorem 3.2], one can show that there is a unique additive mapping A:XY such that

f ( a ) A ( a ) Φ(a,a,2a)

for all aX. The mapping A:XY is given by

A(a)= lim l 1 2 l f ( 2 l a )

for all aX. By Lemma 5.1,

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n f ( x i j ) A ( x i j ) i , j = 1 n Φ( x i j , x i j ,2 x i j )

for all x=[ x i j ] M n (X). Thus A:XY is a unique additive mapping satisfying (5.3), as desired. □

Corollary 5.4 Let r, θ be positive real numbers with r<1. Let f:XY be a mapping such that

f n ( [ x i j ] ) + f n ( [ y i j ] ) + f n ( [ z i j ] ) n f n ( [ x i j ] + [ y i j ] + [ z i j ] ) n + i , j = 1 n θ ( x i j r + y i j r + z i j r )
(5.4)

for all x=[ x i j ],y=[ y i j ],z=[ z i j ] M n (X). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n 2 + 2 r 2 2 r θ x i j r

for all x=[ x i j ] M n (X).

Proof Letting ϕ(a,b,c)=θ( a r + b r + c r ) in Theorem 5.3, we obtain the result. □

Theorem 5.5 Let f:XY be a mapping and let ϕ: X 3 [0,) be a function satisfying (5.2) and

Φ(a,b,c):= 1 2 l = 1 2 l ϕ ( a 2 l , b 2 l , c 2 l ) <+,
(5.5)

for all a,b,cX. Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n Φ( x i j , x i j ,2 x i j )

for all x=[ x i j ] M n (X).

Proof The proof is similar to the proof of Theorem 5.3. □

Corollary 5.6 Let r, θ be positive real numbers with r>1. Let f:XY be a mapping satisfying (5.4). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n 2 r + 2 2 r 2 θ x i j r

for all x=[ x i j ] M n (X).

Proof Letting ϕ(a,b,c)=θ( a r + b r + c r ) in Theorem 5.5, we obtain the result. □

We need the following result.

Lemma 5.7 [42]

If E is an L -matrix normed space, then [ x i j ] n [ x i j ] n for all [ x i j ] M n (E).

Theorem 5.8 Let Y be an L -normed Banach space. Let f:XY be a mapping and let ϕ: X 3 [0,) be a function satisfying (5.1) and

f n ( [ x i j ] ) + f n ( [ y i j ] ) + f n ( [ z i j ] ) n f n ( [ x i j ] + [ y i j ] + [ z i j ] ) n + [ ϕ ( x i j , y i j , z i j ) ] n
(5.6)

for all x=[ x i j ],y=[ y i j ],z=[ z i j ] M n (X). Then there exists a unique additive mapping A:XY such that

[ f ( x i j ) A ( x i j ) ] n [ Φ ( x i j , x i j , 2 x i j ) ] n
(5.7)

for all x=[ x i j ] M n (X). Here Φ is given in Theorem  5.3.

Proof By the same reasoning as in the proof of Theorem 5.3, there exists a unique additive mapping A:XY such that

f ( a ) A ( a ) Φ(a,a,2a)

for all aX. The mapping A:XY is given by

A(a)= lim l 1 2 l f ( 2 l a )

for all aX.

It is easy to show that if 0 a i j b i j for all i, j, then

[ a i j ] n [ b i j ] n .
(5.8)

By Lemma 5.7 and (5.8),

[ f ( x i j ) A ( x i j ) ] n [ f ( x i j ) A ( x i j ) ] n [ Φ ( x i j , x i j , 2 x i j ) ] n

for all x=[ x i j ] M n (X). So, we obtain the inequality (5.7). □

Corollary 5.9 Let Y be an L -normed Banach space. Let r, θ be positive real numbers with r<1. Let f:XY be a mapping such that

f n ( [ x i j ] ) + f n ( [ y i j ] ) + f n ( [ z i j ] ) n f n ( [ x i j ] + [ y i j ] + [ z i j ] ) n + [ θ ( x i j r + y i j r + z i j r ) ] n
(5.9)

for all x=[ x i j ],y=[ y i j ],z=[ z i j ] M n (X). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n [ 2 2 r 2 2 r θ x i j r ] n

for all x=[ x i j ] M n (X).

Proof Letting ϕ(a,b,c)=θ( a r + b r + c r ) in Theorem 5.8, we obtain the result. □

Theorem 5.10 Let Y be an L -normed Banach space. Let f:XY be a mapping and let ϕ: X 3 [0,) be a function satisfying (5.5) and (5.6). Then there exists a unique additive mapping A:XY such that

[ f ( x i j ) A ( x i j ) ] n [ Φ ( x i j , x i j , 2 x i j ) ] n

for all x=[ x i j ] M n (X). Here Φ is given in Theorem  5.5.

Proof The proof is similar to the proof of Theorem 5.8. □

Corollary 5.11 Let Y be an L -normed Banach space. Let r, θ be positive real numbers with r>1. Let f:XY be a mapping satisfying (5.9). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n [ 2 r + 2 2 r 2 θ x i j r ] n

for all x=[ x i j ] M n (X).

Proof Letting ϕ(a,b,c)=θ( a r + b r + c r ) in Theorem 5.10, we obtain the result. □

Theorem 5.12 Let ϕ: X 3 [0,) be a function such that there exists an α<1 with

ϕ(a,b,c)2αϕ ( a 2 , b 2 , c 2 )
(5.10)

for all a,b,cX. Let f:XY be a mapping satisfying (5.2). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n 1 2 2 α ϕ( x i j , x i j ,2 x i j )
(5.11)

for all x=[ x i j ] M n (X).

Proof When n=1, (5.2) is equivalent to

f ( a ) + f ( b ) + f ( c ) f ( a + b + c ) +ϕ(a,b,c)
(5.12)

for all a,b,cX. It follows from (5.12) that

2 f ( a ) f ( 2 a ) ϕ(a,a,2a)
(5.13)

for all aX. So,

f ( a ) 1 2 f ( 2 a ) 1 2 ϕ(a,a,2a)
(5.14)

for all aX.

Consider the set

S:={h:XY}

and introduce the generalized metric on S:

d(g,h)=inf { μ R + : g ( a ) h ( a ) μ ϕ ( a , a , 2 a ) , a X } ,

where, as usual, inf{}=+. It is easy to show that (S,d) is complete (see [40]).

Now we consider the linear mapping J:SS such that

Jg(a):= 1 2 g(2a)

for all aX.

Let g,hS be given such that d(g,h)=ε. Then

g ( a ) h ( a ) ϕ(a,a,2a)

for all aX. Hence

J g ( a ) J h ( a ) = 1 2 g ( 2 a ) 1 2 h ( 2 a ) αϕ(a,a,2a)

for all aX. So, d(g,h)=ε implies that d(Jg,Jh)αε. This means that

d(Jg,Jh)αd(g,h)

for all g,hS.

It follows from (5.14) that d(f,Jf) 1 2 .

By Theorem 1.6, there exists a mapping A:XY satisfying the following:

  1. (1)

    A is a fixed point of J, i.e.,

    A(2a)=2A(x)
    (5.15)

for all xX. The mapping A is a unique fixed point of J in the set

M= { g S : d ( h , g ) < } .

This implies that A is a unique mapping satisfying (5.15) such that there exists a μ(0,) satisfying

f ( a ) A ( a ) μϕ(a,a,2a)

for all aX;

  1. (2)

    d( J l f,A)0 as l. This implies the equality

    lim l 1 2 l f ( 2 l a ) =A(a)

for all aX;

  1. (3)

    d(f,A) 1 1 α d(f,Jf), which implies the inequality

    d(f,A) 1 2 2 α .

So,

f ( a ) A ( a ) 1 2 2 α ϕ(a,a,2a)
(5.16)

for all aX.

It follows from (5.10) and (5.12) that

lim l 1 2 l f ( 2 l a ) + f ( 2 l b ) + f ( 2 l c ) lim l ( 1 2 l f ( 2 l ( a + b + c ) ) + 1 2 l ϕ ( 2 l a , 2 l b , 2 l c ) )
(5.17)

for all a,b,cX.

It follows from (5.17) that

A ( a ) + A ( b ) + A ( c ) A ( a + b + c )

for all a,b,cX. By Lemma 5.2, A:XY is additive.

By Lemma 5.7 and (5.16),

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n f ( x i j ) A ( x i j ) i , j = 1 n 1 2 2 α ϕ( x i j , x i j ,2 x i j )

for all x=[ x i j ] M n (X). Thus A:XY is a unique additive mapping satisfying (5.11), as desired. □

Corollary 5.13 Let r, θ be positive real numbers with r<1. Let f:XY be a mapping satisfying (5.9). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n 2 + 2 r 2 2 r θ x i j r

for all x=[ x i j ] M n (X).

Proof The proof follows from Theorem 5.12 by taking ϕ(a,b,c)=θ( a r + b r + c r ) for all a,b,cX. Then we can choose α= 2 r 1 , and we get the desired result. □

Theorem 5.14 Let f:XY be a mapping satisfying (5.2) for which there exists a function ϕ: X 3 [0,) such that there exists an α<1 with

ϕ(a,b,c) α 2 ϕ(2a,2b,2c)
(5.18)

for all a,b,cX. Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n α 2 2 α ϕ( x i j , x i j ,2 x i j )

for all x=[ x i j ] M n (X).

Proof Let (S,d) be the generalized metric space defined in the proof of Theorem 5.12.

Now we consider the linear mapping J:SS such that

Jg(a):=2g ( a 2 )

for all aX.

It follows from (5.13) that

f ( a ) 2 f ( a 2 ) ϕ ( a 2 , a 2 , a ) α 2 ϕ(a,a,2a)

for all aX. Thus d(f,Jf) α 2 . So,

d(f,A) α 2 2 α .

The rest of the proof is similar to the proof of Theorem 5.12. □

Corollary 5.15 Let r, θ be positive real numbers with r>1. Let f:XY be a mapping satisfying (5.9). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n i , j = 1 n 2 r + 2 2 r 2 θ x i j r

for all x=[ x i j ] M n (X).

Proof The proof follows from Theorem 5.14 by taking ϕ(a,b,c)=θ( a r + b r + c r ) for all a,b,cX. Then we can choose α= 2 1 r , and we get the desired result. □

From now on, assume that Y is an L -normed Banach space.

Theorem 5.16 Let f:XY be a mapping and let ϕ: X 3 [0,) be a function satisfying (5.10) and (5.6). Then there exists a unique additive mapping A:XY such that

[ f ( x i j ) A ( x i j ) ] n [ 1 2 2 α ϕ ( x i j , x i j , 2 x i j ) ] n
(5.19)

for all x=[ x i j ] M n (X).

Proof By the same reasoning as in the proof of Theorem 5.12, there exists a unique additive mapping A:XY such that

f ( a ) A ( a ) 1 2 2 α ϕ(a,a,2a)

for all aX.

By Lemma 5.7 and (5.8),

[ f ( x i j ) A ( x i j ) ] n [ f ( x i j ) A ( x i j ) ] n [ 1 2 2 α ϕ ( x i j , x i j ) ] n

for all x=[ x i j ] M n (X). So, we obtain the inequality (5.19). □

Corollary 5.17 Let r, θ be positive real numbers with r<1. Let f:XY be a mapping satisfying (5.9). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n [ 2 2 r 2 2 r θ x i j r ] n

for all x=[ x i j ] M n (X).

Proof The proof follows from Theorem 5.16 by taking ϕ(a,b,c)=θ( a r + b r + c r ) for all a,b,cX. Then we can choose α= 2 r 1 , and we get the desired result. □

Theorem 5.18 Let f:XY be a mapping and let ϕ: X 3 [0,) be a function satisfying (5.6) and (5.18). Then there exists a unique additive mapping A:XY such that

[ f ( x i j ) A ( x i j ) ] n [ α 2 2 α ϕ ( x i j , x i j , 2 x i j ) ] n

for all x=[ x i j ] M n (X).

Proof The proof is similar to the proof of Theorem 5.16. □

Corollary 5.19 Let r, θ be positive real numbers with r>1. Let f:XY be a mapping satisfying (5.9). Then there exists a unique additive mapping A:XY such that

f n ( [ x i j ] ) A n ( [ x i j ] ) n [ 2 2 + 2 2 r 2 θ x i j r ] n

for all x=[ x i j ] M n (X).

Proof The proof follows from Theorem 5.18 by taking ϕ(a,b,c)=θ( a r + b r + c r ) for all a,b,cX. Then we can choose α= 2 1 r , and we get the desired result. □

References

  1. Katsaras AK: Fuzzy topological vector spaces II . Fuzzy Sets Syst. 1984, 12: 143–154. 10.1016/0165-0114(84)90034-4

    Article  MathSciNet  MATH  Google Scholar 

  2. Felbin C: Finite dimensional fuzzy normed linear spaces. Fuzzy Sets Syst. 1992, 48: 239–248. 10.1016/0165-0114(92)90338-5

    Article  MathSciNet  MATH  Google Scholar 

  3. Krishna SV, Sarma KKM: Separation of fuzzy normed linear spaces. Fuzzy Sets Syst. 1994, 63: 207–217. 10.1016/0165-0114(94)90351-4

    Article  MathSciNet  MATH  Google Scholar 

  4. Xiao JZ, Zhu XH: Fuzzy normed spaces of operators and its completeness. Fuzzy Sets Syst. 2003, 133: 389–399. 10.1016/S0165-0114(02)00274-9

    Article  MathSciNet  MATH  Google Scholar 

  5. Bag T, Samanta SK: Finite dimensional fuzzy normed linear spaces. J. Fuzzy Math. 2003, 11: 687–705.

    MathSciNet  MATH  Google Scholar 

  6. Cheng SC, Mordeson JM: Fuzzy linear operators and fuzzy normed linear spaces. Bull. Calcutta Math. Soc. 1994, 86: 429–436.

    MathSciNet  MATH  Google Scholar 

  7. Kramosil I, Michalek J: Fuzzy metric and statistical metric spaces. Kybernetika 1975, 11: 326–334.

    MathSciNet  MATH  Google Scholar 

  8. Bag T, Samanta SK: Fuzzy bounded linear operators. Fuzzy Sets Syst. 2005, 151: 513–547. 10.1016/j.fss.2004.05.004

    Article  MathSciNet  MATH  Google Scholar 

  9. Mirmostafaee AK, Moslehian MS: Fuzzy versions of Hyers-Ulam-Rassias theorem. Fuzzy Sets Syst. 2008, 159: 720–729. 10.1016/j.fss.2007.09.016

    Article  MathSciNet  MATH  Google Scholar 

  10. Mirmostafaee AK, Mirzavaziri M, Moslehian MS: Fuzzy stability of the Jensen functional equation. Fuzzy Sets Syst. 2008, 159: 730–738. 10.1016/j.fss.2007.07.011

    Article  MathSciNet  MATH  Google Scholar 

  11. Mirmostafaee AK, Moslehian MS: Fuzzy approximately cubic mappings. Inf. Sci. 2008, 178: 3791–3798. 10.1016/j.ins.2008.05.032

    Article  MathSciNet  MATH  Google Scholar 

  12. Ruan ZJ:Subspaces of C -algebras. J. Funct. Anal. 1988, 76: 217–230. 10.1016/0022-1236(88)90057-2

    Article  MathSciNet  MATH  Google Scholar 

  13. Effros E, Ruan ZJ: On approximation properties for operator spaces. Int. J. Math. 1990, 1: 163–187. 10.1142/S0129167X90000113

    Article  MathSciNet  MATH  Google Scholar 

  14. Choi MD, Effros E: Injectivity and operator spaces. J. Funct. Anal. 1977, 24: 156–209. 10.1016/0022-1236(77)90052-0

    Article  MathSciNet  MATH  Google Scholar 

  15. Effros E, Ruan ZJ: On the abstract characterization of operator spaces. Proc. Am. Math. Soc. 1993, 119: 579–584. 10.1090/S0002-9939-1993-1163332-4

    Article  MathSciNet  MATH  Google Scholar 

  16. Pisier G:Grothendieck’s theorem for non-commutative C -algebras with an appendix on Grothendieck’s constants. J. Funct. Anal. 1978, 29: 397–415. 10.1016/0022-1236(78)90038-1

    Article  MathSciNet  MATH  Google Scholar 

  17. Haagerup, U: Decomp. of completely bounded maps. Preprint

  18. Effros E: On multilinear completely bounded module maps. Contemp. Math. 62. In Operator Algebras and Mathematical Physics. (IowaCity, Iowa, 1985) Am. Math. Soc., Providence; 1987:479–501.

    Chapter  Google Scholar 

  19. Ulam SM: A Collection of the Mathematical Problems. Interscience, New York; 1960.

    MATH  Google Scholar 

  20. Hyers DH: On the stability of the linear functional equation. Proc. Natl. Acad. Sci. USA 1941, 27: 222–224. 10.1073/pnas.27.4.222

    Article  MathSciNet  MATH  Google Scholar 

  21. Aoki T: On the stability of the linear transformation in Banach spaces. J. Math. Soc. Jpn. 1950, 2: 64–66. 10.2969/jmsj/00210064

    Article  MathSciNet  MATH  Google Scholar 

  22. Rassias TM: On the stability of the linear mapping in Banach spaces. Proc. Am. Math. Soc. 1978, 72: 297–300. 10.1090/S0002-9939-1978-0507327-1

    Article  MathSciNet  MATH  Google Scholar 

  23. Găvruta P: A generalization of the Hyers-Ulam-Rassias stability of approximately additive mappings. J. Math. Anal. Appl. 1994, 184: 431–436. 10.1006/jmaa.1994.1211

    Article  MathSciNet  MATH  Google Scholar 

  24. Gilányi A: Eine zur Parallelogrammgleichung äquivalente Ungleichung. Aequ. Math. 2001, 62: 303–309. 10.1007/PL00000156

    Article  Google Scholar 

  25. Rätz J: On inequalities associated with the Jordan-von Neumann functional equation. Aequ. Math. 2003, 66: 191–200. 10.1007/s00010-003-2684-8

    Article  MathSciNet  MATH  Google Scholar 

  26. Gilányi A: On a problem by K. Nikodem. Math. Inequal. Appl. 2002, 5: 707–710.

    MathSciNet  MATH  Google Scholar 

  27. Fechner W: Stability of a functional inequalities associated with the Jordan-von Neumann functional equation. Aequ. Math. 2006, 71: 149–161. 10.1007/s00010-005-2775-9

    Article  MathSciNet  MATH  Google Scholar 

  28. Park C, Cho Y, Han M: Functional inequalities associated with Jordan-von Neumann type additive functional equations. J. Inequal. Appl. 2007., 2007: Article ID 41820

    Google Scholar 

  29. Cădariu L, Radu V: Fixed points and the stability of Jensen’s functional equation. J. Inequal. Pure Appl. Math. 2003., 4(1): Article ID 4

  30. Diaz J, Margolis B: A fixed point theorem of the alternative for contractions on a generalized complete metric space. Bull. Am. Math. Soc. 1968, 74: 305–309. 10.1090/S0002-9904-1968-11933-0

    Article  MathSciNet  MATH  Google Scholar 

  31. Isac G, Rassias TM: Stability of ψ -additive mappings: applications to nonlinear analysis. Int. J. Math. Math. Sci. 1996, 19: 219–228. 10.1155/S0161171296000324

    Article  MathSciNet  MATH  Google Scholar 

  32. Cădariu L, Radu V: On the stability of the Cauchy functional equation: a fixed point approach. Grazer Math. Ber. 2004, 346: 43–52.

    MathSciNet  MATH  Google Scholar 

  33. Cădariu L, Radu V: Fixed point methods for the generalized stability of functional equations in a single variable. Fixed Point Theory Appl. 2008., 2008: Article ID 749392

    Google Scholar 

  34. Jung Y, Chang I: The stability of a cubic type functional equation with the fixed point alternative. J. Math. Anal. Appl. 2005, 306: 752–760. 10.1016/j.jmaa.2004.10.017

    Article  MathSciNet  MATH  Google Scholar 

  35. Mirzavaziri M, Moslehian MS: A fixed point approach to stability of a quadratic equation. Bull. Braz. Math. Soc. 2006, 37: 361–376. 10.1007/s00574-006-0016-z

    Article  MathSciNet  MATH  Google Scholar 

  36. Park C: Fixed points and Hyers-Ulam-Rassias stability of Cauchy-Jensen functional equations in Banach algebras. Fixed Point Theory Appl. 2007., 2007: Article ID 50175

    Google Scholar 

  37. Park C: Generalized Hyers-Ulam-Rassias stability of quadratic functional equations: a fixed point approach. Fixed Point Theory Appl. 2008., 2008: Article ID 493751

    Google Scholar 

  38. Radu V: The fixed point alternative and the stability of functional equations. Fixed Point Theory Appl. 2003, 4: 91–96.

    MathSciNet  MATH  Google Scholar 

  39. Cho Y, Park C, Saadati R: Fuzzy functional inequalities. J. Comput. Anal. Appl. 2011, 13: 305–320.

    MathSciNet  MATH  Google Scholar 

  40. Miheţ D, Radu V: On the stability of the additive Cauchy functional equation in random normed spaces. J. Math. Anal. Appl. 2008, 343: 567–572. 10.1016/j.jmaa.2008.01.100

    Article  MathSciNet  MATH  Google Scholar 

  41. Park C: Fixed points and stability of the Cauchy-Jensen functional inequality in fuzzy Banach algebras. Appl. Math. Lett. 2011, 24: 2024–2029. 10.1016/j.aml.2011.05.036

    Article  MathSciNet  MATH  Google Scholar 

  42. Shin D, Lee S, Byun C, Kim S: On matrix normed spaces. Bull. Korean Math. Soc. 1983, 27: 103–112.

    MathSciNet  MATH  Google Scholar 

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Acknowledgements

CP was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (NRF-2012R1A1A2004299) and DYS was supported by the Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (NRF-2010-0021792).

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All authors conceived of the study, participated in its design and coordination, drafted the manuscript, participated in the sequence alignment, and read and approved the final manuscript.

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Park, C., Shin, D.Y. & Lee, J.R. Fuzzy stability of functional inequalities in matrix fuzzy normed spaces. J Inequal Appl 2013, 224 (2013). https://doi.org/10.1186/1029-242X-2013-224

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