1 Introduction

In this paper, we consider the second-order neutral impulsive stochastic evolutionequations with infinite delay (SNISEEIs in short) of the following form:

d [ x ( t ) g ( t , x t ) ] = [ A x ( t ) + f ( t , x t ) ] dt+σ(t, x t )dw(t),tJ:=[0,T],
(1)
x 0 =ϕ B h ,
(2)
x (0)=ψH,
(3)
x( t k )= I k ( x t k ), x ( t k )= I ˜ k ( x t k ),k=1,2,,m.
(4)

Here, the state x() takes values in a separable real Hilbert spaceH with inner product (,) and norm , where A:D(A)HH is the infinitesimal generator of a stronglycontinuous cosine family C(t) on H. The history x t :(,0]H, x t (θ)=x(t+θ), for t0, belongs to the phase space B h . Now, we present the abstract phase space B h . Assume that h:(,0](0,) is a continuous function with l= 0 h(t)dt<. For any a>0, define

B h = { ψ : ( , 0 ] H : ( E ψ ( θ ) 2 ) 1 / 2  is a bounded and measurable  function on  [ a , 0 ]  and  0 h ( s ) sup s θ 0 ( E ψ ( θ ) 2 ) 1 / 2 d s < } .

We endow B h with the norm

ψ B h = 0 h(s) sup s θ 0 ( E ψ ( θ ) 2 ) 1 / 2 ds,for all ψ B h ,

then ( B h , B h ) is a Banach space [1]. Let K be another separable Hilbert space with inner product ( , ) K and norm K . Suppose {w(t):t0} is a given K-valued Wiener process with afinite trace nuclear covariance operator Q0 defined on a complete probability space(Ω,F,P) equipped with a normal filtration { F t } t 0 , which is generated by the Wiener process w.We are also employing the same notation for the operator norm L(K;H), where L(K;H) denotes the space of all bounded linear operatorsfrom K into H. Assume that g,f:J× B h H (i=1,2) and σ:J× B h L Q (K,H) are appropriate mappings specified later. Here, L Q (K,H) denotes the space of all Q-Hilbert-Schmidtoperators from K into H, which will be defined in the nextsection. The initial data ϕ={ϕ(t):<t0} is an F 0 -adapted, B h -valued stochastic process independent of the Wienerprocess w with finite second moment. ψ is an F 0 -adapted, H-valued random variableindependent of the Wiener process w with finite second moment. I k and I ˜ k : B h H are appropriate functions. Moreover, let0= t 0 < t 1 << t m < t m + 1 =T, be given time points and the symbolΔξ(t) represents the jump of the function ξat t, which is defined by Δξ(t)=ξ( t + )ξ( t ).

Stochastic partial differential equations (SPDEs in short) with delay have attractedgreat interest due to their applications in describing many sophisticated dynamicalsystems in physical, biological, medical and social sciences. One can see [25] and the references therein for details. Moreover, to describe the systemsinvolving derivatives with delay, Hale and Lunel [6] introduced the deterministic neutral functional differential equations,which are of great interest in theoretical and practical applications. Taking theenvironmental disturbances into account, Kolmanovskii and Myshkis [7] introduced the neutral stochastic functional differential equations(NSFDEs in short) and gave its applications in chemical engineering and aeroelasticity. The investigation of qualitative properties such as existence,uniqueness and stability for NSFDEs has received much attention. One can see [2, 5, 812] and the references therein. In addition, impulsive effects exist in manyevolution processes in which states are changed abruptly at certain moments of time,involved in such fields as medicine and biology, economics, bioengineering, chemicaltechnology etc. (see [13, 14] and the references therein).

On the other hand, the study of abstract deterministic second-order evolutionsequations governed by the generator of a strongly continuous cosine family wasinitiated by [15] and subsequently studied by [16, 17]. The second-order stochastic differential equations are the right modelin continuous time to account for integrated processes that can be made stationary.For instance, it is useful for engineers to model mechanical vibrations or charge ona capacitor or condenser subjected to white noise excitation through a second-orderstochastic differential equations. There are some interesting works that have beendone on the second-order stochastic differential equations. For example, McKibben [18] investigated the second-order damped functional stochastic evolutionequations. For further work on this topic, one can see Mahmudov and McKibben [19]. Moreover, McKibben [20] established the existence and uniqueness of mild solutions for a class ofsecond-order neutral stochastic evolution equations with finite delay.Balasubramaniam and Muthukumar [21] gave the sufficient conditions for the approximate controllability of thesecond-order neutral stochastic evolution equations with infinite delay. For moredetails of second-order stochastic differential equations, we refer the reader to DaPrato [22] and the references therein.

To the best of our knowledge, there is no work reported in the literature aboutSNISEEIs and the aim of this paper is to close this gap. We aim to establish theexistence of the mild solutions for SNISEEIs by means of the Krasnoselskii-Schaeferfixed point theorem. Two types of stochastic nonlinear wave equations with infinitedelay and impulsive effects are provided to illustrate the obtained results.

The paper is organized as follows. In Section 2, we introduce somepreliminaries. In Section 3, we prove the existence of the mild solutions forSNISEEIs by means of the Krasnoselskii-Schaefer fixed point theorem. InSection 4, we study the continuous dependence of solutions on the initialvalues. Two examples are provided in the last section to illustrate the theory.

2 Preliminaries

In this section, we mention some preliminaries needed to establish our results. Fordetails as regards this section, the reader may refer to Da Prato and Zabczyk [3], Fattorini [16] and the references therein.

Let (Ω,F,P;F) (F= { F t } t 0 ) be a complete filtered probability space satisfyingthat F 0 contains all P-null sets of ℱ. AnH-valued random variable is an ℱ-measurable functionx(t):ΩH and the collection of random variablesS={x(t,ω):ΩH|tJ} is called a stochastic process. Generally, we justwrite x(t) instead of x(t,ω) and x(t):JH in the space of S. Let { e i } i = 1 be a complete orthonormal basis of K.Suppose that {w(t):t0} is a cylindrical K-valued Wiener processwith a finite trace nuclear covariance operator Q0, denote Tr(Q)= i = 1 λ i =λ<, which satisfies Q e i = λ i e i , with e i being a CONS of eigenvectors, and then, w.r.t. thisspectral representation of Q the driving Q-Wiener process can berepresented as w(t)= i = 1 λ i w i (t) e i , where { w i ( t ) } i = 1 are mutually independent one-dimensional standardWiener processes. We assume that F t =σ{w(s):0st}, which is a σ-algebra generated byw and F T =F. Let ψL(K,H) and define

ψ Q 2 =Tr ( ψ Q ψ ) = n = 1 λ n ψ e n 2 .

If ψ Q <, then ψ is called aQ-Hilbert-Schmidt operator. Let L Q (K,H) denote the space of all Q-Hilbert-Schmidtoperators ψ:KH. The completion L Q (K,H) of L(K,H) with respect to the topology induced by the norm Q with ψ Q 2 =(ψ,ψ) is a Hilbert space with the above norm topology.

The collection of all strongly measurable, square-integrable, H-valuedrandom variables, denoted by L 2 (Ω,F,P;H) L 2 (Ω,H), is a Banach space equipped with norm x ( ) L 2 = ( E x ( , ω ) H 2 ) 1 / 2 , where the expectation E is defined byEx= Ω x(ω)dP. Let C(J, L 2 (Ω,H)) be the Banach space of all continuous maps fromJ into L 2 (Ω,H) satisfying the condition sup t J E x ( t ) 2 <. An important subspace is given by L 2 0 (Ω,H)={f L 2 (Ω,H):f is  F 0 -measurable}.

We say that a function x:[ν,τ]H is a normalized piecewise continuous function on[ν,τ] if x is piecewise continuous and leftcontinuous on (ν,τ]. We denote by PC([ν,τ];H) the space formed by the normalized piecewisecontinuous stochastic processes from {x(t):t[ν,τ]}. In particular, we introduce the spacePC formed by all H-valued stochastic processes{x(t):t[0,T]} such that x is continuous att t k , x( t k )=x( t k ) and x( t k + ) exists, for all k=1,,m. In the sequel, we always assume thatPC is endowed with the norm x P C = ( sup s J E x ( s ) 2 ) 1 / 2 . It is clear that (PC, P C ) is a Banach space.

To simplify the notations, we put t 0 =0, t n + 1 =T. For xPC, we denote x ˜ k C([ t k , t k + 1 ]; L 2 (Ω,H)), k=0,1,,n, given by

x ˜ k (t)={ x ( t ) , for  t ( t k , t k + 1 ] , x ( t k + ) , for  t = t k .
(5)

Moreover, for BPC, we denote by B ˜ k , k=0,1,,n, the set B ˜ k ={ x ˜ k :xB}.

Lemma 1 A setBPCis relatively compact inPC, if and only if, the set B ˜ k is relatively compact inC([ t k , t k + 1 ]; L 2 (Ω,H)), for everyk=0,1,,m.

Now, we consider the space

B b = { x : ( , T ] H , x k P C ( J k , H )  and there exist  x ( t k )  and  x ( t k + ) with  x ( t k ) = x ( t k ) , x 0 = φ B h , k = 0 , 1 , 2 , , m } ,

where x k is the restriction of x to J k =( t k , t k + 1 ]. Set b be a semi-norm in B b defined by

x b = x 0 B h + sup 0 s T ( E x ( s ) 2 ) 1 / 2 ,x B b .

Then we have the following useful lemma appearing in [23].

Lemma 2 Assume thatx B b , then fortJ, x t B h . Moreover, we have

l ( E x ( t ) 2 ) 1 / 2 x t B h l sup 0 s t ( E x ( s ) 2 ) 1 / 2 + x 0 B h ,

wherel= 0 h(s)ds<.

Now, let us recall some facts about cosine families of operatorsC(t) and S(t) appeared in [15, 16].

Definition 3 A one parameter family {C(t):tR}L(H,H) satisfying that

  1. (i)

    C(0)=I,

  2. (ii)

    C(t)x is continuous in t on ℝ, for all xH,

  3. (iii)

    C(t+s)+C(ts)=2C(t)C(s), for all t,sR,

is called a strongly continuous cosine family.

The corresponding strongly continuous sine family {S(t):tR}L(H,H) is defined by S(t)x= 0 t C(s)xds, tR, xH.

The generator A:HH of {C(t):tR} is given by Ax= d 2 d t 2 C(t)x | t = 0 for all xD(A)={xH:C()x C 2 (R;H)}.

It is well known that the infinitesimal generator A is a closed, denselydefined operator on H. Such cosine and corresponding sine families andtheir generators satisfy the following properties appearing in Fattorini [16]:

Proposition 4 Suppose that A is the infinitesimal generator of a cosine family of operators{C(t):tR}. Then we have

  1. (i)

    there exist M 1 and α0 such that C(t) M e α | t | and hence S(t) M e α | t | ,

  2. (ii)

    A s r ˆ S(u)xdu=[C( r ˆ )C(s)]x for all 0s r ˆ <,

  3. (iii)

    there exists N 1 such that S(s)S( r ˆ ) N s r ˆ e α | s | ds, for all 0s r ˆ <.

The uniform boundedness principle, together with Proposition 4(i), implies thatboth {C(t):t[0,T]} and {S(t):t[0,T]} are uniformly bounded.

To prove our results, we need the following Krasnoselskii-Schaefer type fixed pointtheorem appearing in [24].

Theorem 5 Let Φ 1 and Φ 2 be two operators of H such that

  1. (i)

    Φ 1 is a strict contraction, and

  2. (ii)

    Φ 2 is completely continuous.

Then either

  1. (1)

    the operator equation Φ 1 x+ Φ 2 x=x has a solution, or

  2. (2)

    the set G={xH:λ Φ 1 ( x λ )+λ Φ 2 x=x} is unbounded for λ(0,1).

3 Existence result

In this section, we aim to give the existence of mild solutions for SNISEEIs (1)-(4).Firstly, let us propose the definition of the mild solution of SNISEEIs (1)-(4).

Definition 6 An F t -adapted stochastic process x:(,T]H is called a mild solution of SNISEEIs (1)-(4) if

  1. (i)

    { x t :tJ} is B h -valued and x() | J PC;

  2. (ii)

    x(t)H has càdlàg paths on tJ a.s. and for each tJ, x(t) satisfies the following integral equation:

    x ( t ) = C ( t ) ϕ ( 0 ) + S ( t ) [ ψ g ( 0 , ϕ ) ] + 0 t C ( t s ) g ( s , x s ) d s + 0 t S ( t s ) f ( s , x s ) d s + 0 t S ( t s ) σ ( s , x s ) d w ( s ) + 0 < t k < t C ( t t k ) I k ( x t k ) + 0 < t k < t S ( t t k ) I ˜ k ( x t k ) ;
  3. (iii)

    x 0 =ϕ, x (0)=ψ.

In this paper, we need the following assumptions:

(H1) The cosine family of operators {C(t):t[0,T]} on H and the corresponding sine family{S(t):t[0,T]} satisfy C ( t ) 2 M, S ( t ) 2 M, t0 for a positive constant M.

(H2) The function f:J× B h H satisfies the following properties:

  1. 1.

    f(,ϕ):JH is strongly measurable for every ϕ B h ;

  2. 2.

    f(t,): B h H is continuous for each tJ;

  3. 3.

    there exist an integrable function m:J[0,) and a continuous nondecreasing function Ψ:[0,)(0,) such that for every (t,ϕ)J× B h , we have

    E f ( t , ϕ ) 2 m(t)Ψ ( ϕ B h 2 ) , lim inf ζ Ψ ( ζ ) ζ =Λ<.

(H3) The function σ:J× B h L Q (K,H) satisfies the following properties:

  1. 1.

    σ(t,): B h L Q (K,H) is continuous for almost all tJ;

  2. 2.

    σ(,x):J L Q (K,H) is strongly F t -measurable for each x B h ;

  3. 3.

    there exists a positive constant L σ such that

    E σ ( t , x 1 ) σ ( t , x 2 ) 2 L σ x 1 x 2 B h 2 , ( t , x i ) J × B h , i = 1 , 2 ; E σ ( t , x ) 2 L σ ( x B h 2 + 1 ) , ( t , x ) J × B h .

(H4) The function g:J× B h H is continuous and there exists a positive constant L g such that

E g ( t , x 1 ) g ( t , x 2 ) 2 L g x 1 x 2 B h 2 , ( t , x i ) J × B h , i = 1 , 2 ; E g ( t , x ) 2 L g ( x B h 2 + 1 ) , ( t , x ) J × B h .

(H5) The functions I k and I ˜ k : B h H are continuous and there are positive constants L I k , L I ˜ k , k=1,2,,m such that

E I k ( x ) I k ( y ) 2 L I k x y B h 2 , x , y B h , k = 1 , 2 , , m , E I ˜ k ( x ) I ˜ k ( y ) 2 L I ˜ k x y B h 2 , x , y B h , k = 1 , 2 , , m .

The main result of this section is the following theorem.

Theorem 7 Assume the conditions (H1)-(H5) hold and assume thatS(t)is compact. Then there exists a mild solution of SNISEEIs (1)-(4)provided that

12M l 2 [ T Λ 0 T m ( s ) d s + 2 k = 1 m ( L I k + L I ˜ k ) + 2 T ( T L g + Tr ( Q ) L σ ) ] <1
(6)

and

L 0 =8M l 2 [ T ( T L g + Tr ( Q ) L σ ) + k = 1 m ( L I k + L I ˜ k ) ] <1.
(7)

Proof In the sequel, the notation B r (x,Z) stands for the closed ball with center at xand radius r>0 in Z, where (Z, Z ) is a Banach space. Let y:(,T]H be defined by

y(t)={ ϕ ( t ) , t ( , 0 ] , C ( t ) ϕ ( 0 ) + S ( t ) ψ , t J .

On the space Y={xPC:x(0)=ϕ(0)} endowed with the uniform convergence topology, wedefine the operator Φ:YY by

Φ x ( t ) = C ( t ) ϕ ( 0 ) + S ( t ) [ ψ g ( 0 , ϕ ) ] + 0 t C ( t s ) g ( s , x ¯ s ) d s + 0 t S ( t s ) f ( s , x ¯ s ) d s + 0 t S ( t s ) σ ( s , x ¯ s ) d w ( s ) + 0 < t k < t C ( t t k ) I k ( x ¯ t k ) + 0 < t k < t S ( t t k ) I ˜ k ( x ¯ t k ) , t J ,

where x ¯ is such that x ¯ 0 =ϕ and x ¯ =x on J. From Lemma 2 and the assumptionon ϕ, we infer that ΦxPC. Our proof will be split into the following threesteps.

Step 1. In what follows, we prove that there exists r>0 such that Φ( B r (y | J ,Y)) B r (y | J ,Y). In fact, if it is not true, then for eachr>0 there exist x r B r (y | J ,Y) and t r J such that r<E Φ ( x r ( t r ) ) y ( t r ) 2 . Therefore, from Lemma 2 and the assumptions, wehave

r 2 < E Φ ( x r ( t r ) ) y ( t r ) 2 6 E S ( t r ) g ( 0 , ϕ ) 2 + 6 E ( 0 t r C ( t r s ) g ( s , x ¯ s r ) d s ) 2 + 6 E ( 0 t r S ( t r s ) f ( s , x ¯ s r ) d s ) 2 + 6 M Tr ( Q ) E 0 t r σ ( s , x ¯ s r ) 2 d s + 6 E ( 0 < t k < t C ( t t k ) I k ( x ¯ t k r ) ) 2 + 6 E ( 0 < t k < t S ( t t k ) I ˜ k ( x ¯ t k r ) ) 2 12 M L g ( ϕ B h 2 + 1 ) + 6 T M E 0 t r g ( s , x ¯ s r ) 2 d s + 6 T M E 0 t r f ( s , x ¯ s r ) 2 d s + 6 M Tr ( Q ) E 0 t r σ ( s , x ¯ s r ) 2 d s + 6 M 0 < t k < t E ( I k ( x ¯ t k r ) ) 2 + 6 M 0 < t k < t E ( I ˜ k ( x ¯ t k r ) ) 2 12 M L g ( ϕ B h 2 + 1 ) + 12 T M E 0 t r g ( s , x ¯ s r ) g ( s , y s ) 2 d s + 12 T M E 0 t r g ( s , y s ) 2 d s + 6 T M E 0 t r f ( s , x ¯ s r ) 2 d s + 12 M Tr ( Q ) E 0 t r σ ( s , x ¯ s r ) σ ( s , y s ) 2 d s + 12 M Tr ( Q ) E 0 t r σ ( s , y s ) 2 d s + 12 M 0 < t k < t E [ I k ( x ¯ t k r ) I k ( y t k ) 2 + I k ( y t k ) 2 ] + 12 M 0 < t k < t E [ I ˜ k ( x ¯ t k r ) I ˜ k ( y t k ) 2 + I ˜ k ( y t k ) 2 ] 12 M L g ( ϕ B h 2 + 1 ) + 24 l 2 M ( T L g + Tr ( Q ) L σ ) 0 t r sup 0 u s E x ¯ r ( u ) y ( u ) 2 d s + 24 M ( T L g + Tr ( Q ) L σ ) 0 t r ( y s B h 2 + 1 ) d s + 6 T M E 0 t r m ( s ) Ψ ( 2 ϕ B h 2 + 2 l 2 ( r 2 + y T 2 ) ) d s + 24 l 2 M r 2 k = 1 m [ L I k + L I ˜ k ] + 12 M k = 1 m [ E I k ( y t k ) 2 + E I ˜ k ( y t k ) 2 ] ,

where y T = sup 0 s T Ey(s). Dividing both sides by r 2 and taking the limit as r, we obtain

112M l 2 [ T Λ 0 T m ( s ) d s + 2 k = 1 m ( L I k + L I ˜ k ) + 2 T ( T L g + Tr ( Q ) L σ ) ] ,

which contradicts (6). Thus, for some positive number r,Φ( B r (y | J ,Y)) B r (y | J ,Y). In what follows, we aim to show that the operatorΦ has a fixed point on B r (y | J ,Y), which implies that (1)-(4) has a mild solution. Tothis end, we decompose Φ as Φ= Φ 1 + Φ 2 , where Φ 1 , Φ 2 are defined on B r (y | J ,Y), respectively, by

( Φ 1 x ) ( t ) = C ( t ) ϕ ( 0 ) + S ( t ) [ ψ g ( 0 , ϕ ) ] + 0 t C ( t s ) g ( s , x ¯ s ) d s + 0 t S ( t s ) σ ( s , x ¯ s ) d w ( s ) + 0 < t k < t C ( t t k ) I k ( x ¯ t k ) + 0 < t k < t S ( t t k ) I ˜ k ( x ¯ t k )

and

( Φ 2 x)(t)= 0 t S(ts)f(s, x ¯ s )ds,

for tJ. We will show that Φ 1 is a contraction and Φ 2 is completely continuous.

Step 2. Φ 1 is a contraction. Let x,y B r (y | J ,Y). Then, for each tJ, we have

E ( Φ 1 x ) ( t ) ( Φ 1 y ) ( t ) 2 4 E 0 t C ( t s ) [ g ( s , x ¯ s ) g ( s , y ¯ s ) ] d s 2 + 4 E 0 t S ( t s ) [ σ ( s , x ¯ s ) σ ( s , y ¯ s ) ] d w ( s ) 2 + 4 E 0 < t k < t C ( t t k ) ( I k ( x ¯ t k ) I k ( y ¯ t k ) ) 2 + 4 E 0 < t k < t S ( t t k ) ( I ˜ k ( x ¯ t k ) I ˜ k ( y ¯ t k ) ) 2 4 M ( T L g + Tr ( Q ) L σ ) 0 t x ¯ s y ¯ s B h 2 d s + 4 M k = 1 m ( L I k + L I ˜ k ) x ¯ t k y ¯ t k B h 2 8 M l 2 ( T L g + Tr ( Q ) L σ ) 0 t sup 0 u s E x ¯ ( u ) y ¯ ( u ) B h 2 d s + 8 M l 2 k = 1 m sup 0 s T E x ¯ ( s ) y ¯ ( s ) 2 ( L I k + L I ˜ k ) .

Therefore, we get

( Φ 1 x ) ( t ) ( Φ 1 y ) ( t ) P C 2 L 0 x ¯ y ¯ P C 2 ,

where L 0 =8M l 2 [T(T L g +Tr(Q) L σ )+ k = 1 m ( L I k + L I ˜ k )]. Thus, we obtain

Φ 1 x Φ 1 y P C 2 L 0 x y P C 2 .

By (7), we see that Φ 1 is a contraction on B r (y | J ,Y).

Step 3. Φ 2 is completely continuous on B r (y | J ,Y).

Claim 1 Φ 2 maps bounded sets to bounded sets in B r (y | J ,Y).

In the sequel, r , r are the numbers defined by r :=2 l 2 sup 0 s t (E x ( s ) 2 )+2 ϕ B h 2 and r :=MΨ( r ) 0 t m(s)ds, respectively.

E ( Φ 2 x ) ( t ) 2 0 t s ( t s ) 2 E f ( s , x ¯ s ) 2 d s M 0 t m ( t ) Ψ ( x ¯ s B h 2 ) d s M 0 t m ( t ) Ψ ( 2 l 2 sup 0 s t ( E x ( s ) 2 ) + 2 ϕ B h 2 ) d s M Ψ ( r ) 0 t m ( s ) d s = r ,

which shows the desired result of the claim.

Claim 2 The set of functions Φ 2 ( B r (y | J ,Y))is equicontinuous on J.

Let ε>0 small enough and 0< t 1 < t 2 . We get

E ( Φ 2 x ) ( t 2 ) ( Φ 2 x ) ( t 1 ) 2 3 T 0 t 1 ε S ( t 2 s ) S ( t 1 s ) 2 E f ( s , x ¯ s ) 2 d s + 3 ε t 1 ε t 1 S ( t 2 s ) S ( t 1 s ) 2 E f ( s , x ¯ s ) 2 d s + 3 ( t 2 t 1 ) t 1 t 2 S ( t 2 s ) 2 E f ( s , x ¯ s ) 2 d s 3 T Ψ ( r ) 0 t 1 ε S ( t 2 s ) S ( t 1 s ) 2 m ( s ) d s + 3 ε Ψ ( r ) t 1 ε t 1 S ( t 2 s ) S ( t 1 s ) 2 m ( s ) d s + 3 ( t 2 t 1 ) Ψ ( r ) t 1 t 2 S ( t 2 s ) 2 m ( s ) d s ,

which proves that Φ 2 ( B r (y | J ,Y)) is equicontinuous on J.

Claim 3 Φ 2 maps( B r (y | J ,Y))into a precompact set in( B r (y | J ,Y)). That is, for each fixedtJ, the setV(t)={ Φ 2 z(t):z( B r (y | J ,Y))}is precompact in( B r (y | J ,Y)).

Obviously, V(0)={ Φ 2 (0)}. Let t>0 fixed and for 0<ε<t, define

( Φ 2 ε x ) (t)=S(ε) 0 t ε S(tεs)f(s, x ¯ s )ds.

Since S(t) is a compact operator, the set V ε (t)={ Φ 2 ε x(t):x( B r (y | J ,Y))} is relatively compact in H for everyε, 0<ε<t. Moreover, for each x( B r (y | J ,Y)), we have

E ( Φ 2 x ) ( t ) ( Φ 2 ε x ) ( t ) 2 ε t ε t S ( t s ) 2 E f ( s , x ¯ s ) 2 d s M ε t ε t m ( t ) Ψ ( x ¯ s B h 2 ) d s M Ψ ( r ) ε t ε t m ( s ) d s .

Therefore, we have

E ( Φ 2 x ) ( t ) ( Φ 2 ε x ) ( t ) 2 0,as ε 0 + ,

and there are precompact sets arbitrary close to the set V(t)={ Φ 2 x(t):x( B r (y | J ,Y))}. Thus, the set V(t)={ Φ 2 x(t):x( B r (y | J ,Y))} is precompact in ( B r (y | J ,Y)). Therefore, from the Arzela-Ascoli theorem, theoperator Φ 2 is completely continuous. From Theorem 5, weinfer that there exists a mild solution for the system (1)-(4).  □

4 Examples

In this section, two types of stochastic nonlinear wave equations with infinite delayand impulsive effects are provided to illustrate the theory obtained.

Example 8 We consider the following second-order stochastic Volterraintegro-differential equations with initial-boundary conditions and impulsiveeffects:

d [ x ( t , ξ ) t t K 1 ( t , s ) F 1 ( x ( s , ξ ) ) d s ] = 2 x ( t , ξ ) ξ 2 d t + ( t K 2 ( t , s ) F 2 ( x ( s , ξ ) ) d s ) d t + ( t K 3 ( t , s ) F 3 ( x ( s , ξ ) ) d s ) d w ( t ) , 0 < ξ < π , 0 t T , t t k , k = 1 , 2 , , m ,
(8)
x(t,ξ)=ϕ(t,ξ),<t0,0<ξ<π,
(9)
x(t,0)=x(t,π)=0,0tT,
(10)
x ( 0 , ξ ) t = x 1 (ξ),0<ξ<π,
(11)
x ( t k + ) x ( t k ) = I k ( x ( t k ) ) , x ( t k + ) x ( t k ) = I ˜ k ( x ( t k ) ) , k = 1 , 2 , , m ,
(12)

where w(t) is a standard cylindrical Wiener process in ℝdefined on the probability space (Ω,F,P).

Let H= L 2 [0,π]. The operator A is defined by

(Az)(ξ)= d 2 z ( ξ ) d ξ 2 ,with domain D(A)= { z H : z ( 0 ) = z ( π ) } .

The spectrum of A consists of the eigenvalues n 2 for nN, with associated eigenvectors z n (ξ)= ( 2 π ) 1 / 2 sin(nξ). Furthermore, the set { z n ;nN} is an orthonormal basis of H. In particular,

Ax= n = 1 n 2 x, z n z n ,xD(A).

The operators C(t) defined by

C(t)x= n = 1 cos(nt)x, z n z n ,tR,

form a cosine function on H, with associated sine function

S(t)x= n = 1 sin ( n t ) n x, z n z n ,tR.

From [17], for all xH, tR, S(t)1 and C(t)1.

Let K i (t,s)C( R 2 ,R), i=1,2,3 and assume that there exists a positive continuousfunction f(s) on R such that

| K i (t,t+s)|f(s),i=1,2,3, l 0 = 0 f(s)ds<.

Now, we give the phase space B h . Assume that h:(,0](0,) is a continuous function with l= 0 h(t)dt<. For any a>0, define

B h = { ψ : ( , 0 ] H : ( E | ψ ( θ ) | 2 ) 1 / 2  is a bounded and measurable function on  [ a , 0 ]  and  0 h ( s ) ( E | ψ ( s ) | 2 ) 1 / 2 d s < } .

We endow B h with the norm

ψ B h = 0 h(s) ( E | ψ ( s ) | 2 ) 1 / 2 ds,for all ψ B h .

Then ( B h , B h ) is a Banach space. Let

ϕ ( ξ ) = 0 h ( s ) ϕ ( s , ξ ) d s , g ( t , ϕ ) ( ξ ) = 0 K 1 ( t , t + s ) F 1 ( ϕ ( s , ξ ) ) d s , f ( t , ϕ ) ( ξ ) = 0 K 2 ( t , t + s ) F 2 ( ϕ ( s , ξ ) ) d s , σ ( t , ϕ ) ( ξ ) = 0 K 3 ( t , t + s ) ( ϕ ( s , ξ ) ) d s .

Then (8)-(12) can be rewritten in the abstract form (1)-(4). We can propose suitableconditions on the coefficients appeared in the above equation to guarantee (8)-(12)has at least one mild solution by means of Theorem 7.

Example 9 We consider the following stochastic nonlinear wave equation withimpulsive effects and infinite delay:

d [ x ( t , ξ ) t f 1 ( t , x ( t r , ξ ) ) ] = 2 x ( t , ξ ) ξ 2 d t + f 2 ( t , x ( t r , ξ ) ) d t + σ ( t , x ( t r , ξ ) ) d w ( t ) , 0 ξ π , 0 t T , r > 0 , t t k , k = 1 , 2 , , m ,
(13)
x(t,ξ)=ϕ(t,ξ),<t0,0<ξ<π,
(14)
x(t,0)=x(t,π)=0,0tT,
(15)
x ( 0 , ξ ) t = x 1 (ξ),0<ξ<π,
(16)
x ( t k + ) x ( t k ) = I k ( x ( t k ) ) , x ( t k + ) x ( t k ) = I ˜ k ( x ( t k ) ) , k = 1 , 2 , , m ,
(17)

where x 1 L 0 2 (Ω;H), ϕ B h , B h is defined as Example 8, H= L 2 ([0,π]), and w is an H-valued Wienerprocess.

Let A, C(t) and S(t) be defined as Example 8. Then the above system(13)-(17) can be rewritten in the form of (1)-(4). Further, we assume that f i :[0,T]×RR (i=1,2), σ:[0,T]×RBL(H) and I k , I ˜ k satisfy (H2)-(H5). Then (13)-(17) has at least onemild solution.

Author’s contributions

The author is the only person who is responsible to this work.