Existence and Uniqueness of Mild Solutions for Nonlinear Stochastic Impulsive Differential Equation

and Applied Analysis 3 Definition 2.1. The functions f and g are said to be L2-Carathéodory if 1 f t, x and g t, x are measurable in t and continuous in the second variable a.e. t ∈ J , 2 for each positive constant q, there exists a square integrable function hq : J → R such that ∥ ∥f t, u ∥ ∥ ∨ ∥g t, u ∥ ≤ hq t , ‖u‖ ≤ q, a.e. t ∈ J. 2.2 Motivated by 1, 7 , let us start by defining what we mean by a mild solution of 2.1 . Definition 2.2. AR-valued stochastic process x t x t,w ∈ L2 J, R defined on J is said to be a mild solution of 2.1 with initial value x 0 z if the following conditions are satisfied 1 x t,w is measurable as a function from J ×Ω to R and x t is Ft-adapted; 2 E‖x‖ <∞ for each t ∈ J ; 3 for each z ∈ L2 J, R , the process x satisfies the following integral equation: x t z ∫ t 0 f s, x s ds ∫ t 0 g s, x s dB s ∑ 0<τk<t Ik x τk . 2.3 Our main result is based on the following fixed point theorem of Schaefer. Lemma 2.3 Schaefer fixed-point theorem . Let C, ‖ · ‖ be a convex subset of a normal linear space, and let the operator A : C → C be completely continuous. Define F A {x ∈ C : x λAx, λ ∈ 0, 1 }. 2.4 Then, either 1 the set F A is unbounded or 2 the operator A has a fixed point in C. 3. Main Results We are now in a position to state and prove our existence result of 2.1 . Throughout this paper, we make the following assumptions. H1 The functions f : J × R → R and g : J × R → Rn×l are L2-Carathéodory. H2 There exist positive constants ck, k 1, 2, . . . , m, such that ‖Ik x ‖ ≤ ck, x ∈ L2 J, R . 3.1 H3 There exists a square integrable function p : J → R and a continuous nondecreasing function ψ : 0,∞ → 0,∞ such that ∥f t, x ∥∥ ∨ ∥g t, x ∥ ≤ p t ψ ‖x‖ , t ∈ J, x ∈ L2 J, R , 3.2 4 Abstract and Applied Analysis with 4 ∫b 0 b 1 p2 s ds < ∫∞


Introduction
Impulsive dynamical systems often exhibit continuous evolutions typically described by ordinary differential equations and instantaneous state jumps.Since many evolution processes, optimal control models in economics, stimulated neural networks, frequencymodulated systems, and some motions of missiles or aircrafts are characterized by the impulsive dynamical behavior, the study of impulsive systems is of great importance.Nowadays, there has been increasing interest in the analysis and synthesis of impulsive systems due to their significance both in theory and applications; see 1-4 and the references therein.
On the other hand, stochastic differential equations SDEs have attracted a great attention since they have been used extensively in many areas of application including finance and social science.Existence, uniqueness, and qualitative analysis of solutions of SDEs have been considered by many authors; see, for example, 5, 6 and Oksendal 7 .In particular, 7 has obtained sufficient conditions uniform Lipschitz condition and the linear growth condition on the existence and uniqueness of solution of SDEs.With the same conditions, Mao 8 has also proved there exists a unique solution for neutral stochastic functional differential equations with finite delay, and systems with infinite delay was investigated by 9 under uniform Lipschitz condition and moment estimate.
Furthermore, besides impulsive effects, stochastic effects likewise exist in real systems.Therefore, stochastic impulsive differential equations SIDEs describing these dynamical systems subject to both stochastic and impulse changes have attracted considerable attention 10-14 .Liu et al. 10 has proved the existence and uniqueness with Lipschitz and linear growth condition by continuation method.Results of existence and uniqueness were obtained by stochastic Lyapunov-type method in 11, 12 .Besides that, the existing literature of SIDEs involved mainly the issue on controllability and stability see 13, 14 , and little investigation, to our best knowledge, has been carried out for existence and uniqueness of general nonlinear systems with stochastic impulsive structure.Unlike the previous results in 10-12 , this paper will deal with the situation when the drift and diffusion coefficients do not satisfy Lipschitz condition.Sufficient conditions of existence and uniqueness of mild solutions for general nonlinear SIDEs are developed based on the Schaefer's fixed point theorem instead of employing stochastic Lyapunov-type function.In addition, some known results can been considered as special cases of the main theorems in this paper.
The organization of this paper is as follows.In Section 1, we will recall briefly some basic notations and preliminary facts which will be used throughout the paper.In Section 2, sufficient conditions are obtained on existence and uniqueness of mild solutions to SIDEs.A numerical example is given to illustrate the proposed conditions in Section 3. Finally, concluding remarks are presented in Section 4.

Preliminaries
Let • denote the Euclidean norm in R n .If A is a matrix, its Frobenius norm is represented by A tr A T A .{Ω, F, P} stands for a complete probability space with a filtration {F t } t≥0 satisfying the usual conditions i.e., right continuous and F 0 containing all P-null sets .Assume that B t B 1 t , B 2 t , . . ., B l t T is an l-dimensional Brownian motion defined on {Ω, F, P}.Denote L F 2 J, R n as the family of all square integrable and F t adapted measurable processes x t x t, w mapping J is the Banach space with the norm topology given by x t 2 * sup 0≤s≤t E x s 2 .Consider stochastic differential equations with impulsive effects as follows: where Definition 2.1.The functions f and g are said to be L 2 -Carathéodory if 1 f t, x and g t, x are measurable in t and continuous in the second variable a.e.t ∈ J, 2 for each positive constant q, there exists a square integrable function h q : J → R such that 3 for each z ∈ L F 2 J, R n , the process x satisfies the following integral equation: Our main result is based on the following fixed point theorem of Schaefer.
Lemma 2.3 Schaefer fixed-point theorem .Let C, • be a convex subset of a normal linear space, and let the operator A : C → C be completely continuous.Define Then, either 1 the set F A is unbounded or 2 the operator A has a fixed point in C.

Main Results
We are now in a position to state and prove our existence result of 2.1 .Throughout this paper, we make the following assumptions.

3.1
H 3 There exists a square integrable function p : J → R and a continuous nondecreasing function ψ : 0, ∞ → 0, ∞ such that where c 4E z 2 .
Theorem 3.1.Assume that H 1 -H 3 hold, then there is at least one solution of 2.1 on J.
Proof.For any x t ∈ L F 2 J, R n , define the operator P by By Lemma 2.3, we will first show that the operator P is completely continuous. Step

3.5
By the Bunyakovskii inequality, one has and by the It ô isometry it follows that Hence, it can be obtained directly from 3.5 -3.7 that

3.8
Since f is L 2 -Carath éodory and I k are continuous functions, by the Lebesgue dominated convergence theorem, we see 3.9 Step 2. P maps bounded sets into bounded sets.That is enough to prove that there exists a positive constant θ such that for each

3.10
Step 3. P maps bounded sets into equicontinuous sets of

3.11
As t 2 → t 1 , the right-hand side of the inequality above tends to zero.The case 0 < t 2 < t 1 ≤ b can be considered in a similar manner.From Ascoli-Arzela theorem and Steps 1 to 3, the operator P is completely continuous.To complete the proof of the theorem, it suffices to prove the following step.
Step 4.There exists a priori bound of the set F P x ∈ L F 2 J, R n , x λP x for some λ ∈ 0, 1 .

3.12
Let x t ∈ F P , then x t λP x t for some 0 < λ < 1.Thus, for each t ∈ J, which implies that

3.14
Consider the function μ t defined by

3.15
With the previous inequality, we have for

3.16
Take the right-hand side of the inequality above as v t , then we get and, moreover, Hence, there exists a constant k such that v t ≤ k, t ∈ J, that is, μ t x t 2 * ≤ v t ≤ k, t ∈ J, which implies that F P is bounded.From the Schaefer's fixed theorem, we deduce that P has a fixed point x t which is a solution to 2.1 .The proof is completed.
In this part, in order to attain the uniqueness result of 2.1 , we propose the following assumptions.
A 1 There exists a square integrable function l t : J → R such that, for all x, y ∈ L F 2 R n and t ∈ J, f t, x − f t, y ∨ g t, x − g t, y ≤ l t x − y .

3.25
Hence, P is a contraction and it has a unique fixed point which is a solution to 2.1 .The proof is completed.
Remark 3.3.Note that the existence and uniqueness result in 7 can be inferred from Theorems 3.1 and 3.2 in case that I k 0 in 2.1 .Furthermore, if the systems in 9 and 2.1 are both reduced to the impulsive differential equations, then we can deduce the results on existence and uniqueness in 9 directly from Theorems 3.1 and 3.2.And, if the delay 0 in 2 , then the conditions there can be inferred from Theorems 3.1 and 3.2 in case that g 0 in 2.1 .

Example
Consider the following stochastic impulsive differential equation: where I 1 x 1/4 arctan x with I 1 x ≤ π/8 and Assume that p t 1 t t 3 and ψ x x, then it can be easily verified that the conditions H 1 -H 3 are satisfied, and by, Theorem 3.1, 4.1 has at least one solution.
For all x, y ∈ L F 2 J, R n and t ∈ 0, 1 , set l t 1 t t 3 , then f t, x − f t, y ∨ g t, x − g t, y ≤ l t x − y .

4.3
As stated in 4.2 , d k 1/4 < 1; hence, 4.1 has a unique solution by Theorem 3.2.As demonstrated in the example, if f or g takes the form such as p t x 2 , then inequality 3.3 in hypothesis H 3 cannot hold.Based on this observation, in the subsequent research, some useful tools and conditions such as locally Lipschitz condition will be considered to relax restrictions on f and g.

Conclusion
By using Schaefer's fixed theorem, this paper has obtained sufficient conditions of existence and uniqueness of mild solutions to general nonlinear stochastic impulsive differential equations.In addition, some known results about systems without delay or impulse can be considered as special cases of the main theorems.
Assume that (A 1 )-(A 2 ) hold, then there exists a unique solution to 2.1 if m k 1 d k < 1.Proof.Let P be an operator defined as in 3.4 .To prove that P is contractive, introduce the Bielecki-type norm on L F 2 J, R n defined by