The Existence and Stability of Inclusion Equations Type of Stochastic Dynamical System Driven by Mixed Fractional Brownian Motion in a Real Separable Hilbert Space
Salah H Abid1, Sameer Q Hasan1,, Zainab A Khudhur1
1Department of Mathematics, College of Education Almustansryah University
Abstract
In this paper we presented The existence and stability of inclusion equations type of stochastic dynamical system driven by mixed fractional Brownian motion in a real separable Hilbert space with an illustrative example.
Keywords: stochastic dynamical system, mixed fractional Brownian motion, mixed-stochastic mild solution, fractional partial differential equations, Asymptotic Stability, real separable Hilbert space
Copyright © 2017 Science and Education Publishing. All Rights Reserved.Cite this article:
- Salah H Abid, Sameer Q Hasan, Zainab A Khudhur. The Existence and Stability of Inclusion Equations Type of Stochastic Dynamical System Driven by Mixed Fractional Brownian Motion in a Real Separable Hilbert Space. Applied Mathematics and Physics. Vol. 5, No. 1, 2017, pp 1-10. https://pubs.sciepub.com/amp/5/1/1
- Abid, Salah H, Sameer Q Hasan, and Zainab A Khudhur. "The Existence and Stability of Inclusion Equations Type of Stochastic Dynamical System Driven by Mixed Fractional Brownian Motion in a Real Separable Hilbert Space." Applied Mathematics and Physics 5.1 (2017): 1-10.
- Abid, S. H. , Hasan, S. Q. , & Khudhur, Z. A. (2017). The Existence and Stability of Inclusion Equations Type of Stochastic Dynamical System Driven by Mixed Fractional Brownian Motion in a Real Separable Hilbert Space. Applied Mathematics and Physics, 5(1), 1-10.
- Abid, Salah H, Sameer Q Hasan, and Zainab A Khudhur. "The Existence and Stability of Inclusion Equations Type of Stochastic Dynamical System Driven by Mixed Fractional Brownian Motion in a Real Separable Hilbert Space." Applied Mathematics and Physics 5, no. 1 (2017): 1-10.
Import into BibTeX | Import into EndNote | Import into RefMan | Import into RefWorks |
1. Introduction
The theory of integro-differential equations or inclusions has become an active area of investigation due to their applications in the fields such as mechanics, electrical engineering, medicine biology, ecology and so on, On can see [1, 4, 14] and references therein. Several authors have established the existence results of mild solutions for these equations (see [3, 7, 9, 11, 14] and references therein). In addition, the nonlinear integro-differential equations with resolvent operators serve as an abstract formulation of partial integro-differential equations that arise in many physical phenomena. One can see [16] and references therein. The deterministic models often fluctuate due to noise, which is random or at least appears to be so. Therefore, we must move from deterministic problems to stochastic problems. As the generalization of classic impulsive integro-differential equations or inclusions, impulsive neutral stochastic functional integro-differential equations or inclusions have attracted the researchers great interest. And some works have done on the existence results of mild solutions for these equations (see [12, 17] and references therein). To the best of our knowledge, there is no work reported on the existence of mild solutions for the impulsive neutral stochastic functional integro-differential inclusions with nonlocal initial conditions and resolvent operators, and the aim of this paper is to close the gap. In this paper, motivated by the previously mentioned papers, we will study this interesting problem. Sufficient conditions for the existence are given by means of the fixed point theorem for multi-valued mapping due to Dhage [6] and the fractional power of operators. Especially, the known results appeared in [2, 8, 10, 12, 15] and [5, 6, 11, 16] are generalized to the stochastic settings. An example is provided to illustrate the theory.
2. Preliminaries
For more details on this section, We refer the reader to Da prato and Zabczyk [13] throughout the paper and
denote two real separable Hilbert spaces. In case without confusion, we just use
for the inner product and
for the norm.
Let be complete filtered probability space satisfying that
contains all
-null sets of
. An
-valued random variable is an
-measurable function
and the collection of random variables
is called a stochastic process. Generally, we just write
instead of
and
in the space of S. Let
be a complete orthonormal basis of
. Suppose that
is a cylindrical
valued wiener process with a finite trace nuclear covariance operator
denote
which satisfies that
So, actually,
where
are mutually independent one-dimensional standard wiener processes. We assume that
is the
algebra generated by w and
. Let
and define
If then
is called a
-Hilbert-Schmidt operator. Let
denote the space of all
-Hilbert-Schmidt operators
The completion
of
with respect to topology induced by the norm
where
is a Hilbert space with the above norm topology. Let
be infinitesimal generator of a compact, analytic resolvent operator
Let
denote the Hilbert space of all
measurable square integrable random variables with values in
. Let
be the Hilbert space of all square integrable and
measurable processes with values in
let
denote the family of all
measurable,
–valued random variables
We use the notations
for the family of all subsets of
and denote
![]() |
In what follows, we briefly introduce some facts on multi-valued analysis. For details, one can see [10]. A multi-valued map is convex (closed) valued, if
is convex (closed)for all
.
is bounded on bounded sets if
is bounded in H, for any bounded set B of H, that is,
is called upper semi continuous (u.s.c. for short ) on
, if for any
, the set
is a nonempty, closed subset of H, and if for each open set B of
containing
there exists an open neighborhood N of x such that
is said to be completely continuous if
is relatively compact, for every bounded subset
If the multi –valued map
is completely continuous with nonempty compact values, then
is u.s.c. if and only if
has a closed graph, i.e.,
.
has a fixed point if there is
such that
A multi-valued map
is said to be measurable if for each
the mean –square distance between
and
is measurable.
Definition (1) (following in [5])
Let be a filtered probability space.
(i) The filtration is said to be complete if
is a complete and if
contains all the
null sets.
(ii) The filtration, is said to satisfy the usual hypotheses if it is complete and right continuous, that is
where
.
Lemma (1) (following in [1])
Let be a compact interval and a Hilbert space. Let
be an
Caratheodory multi-valued map with
and let
be a linear continuous mapping from
to
Then, the operator
is a closed graph operator in
where
is known as the selectors set from
, is given by
.
Lemma (2), (Ito isometry theorem) (following in [20])
Let be the class of functions such that
,
is measurable,
adapted and
. Then for every
![]() |
where is a wiener process.
Definition (2) (following in [12])
Let be a constant belonging to (0, 1). A one dimensional fractional Brownian motion
of Hurst index
is a continuous and centered Gaussian process with covariance function
![]() |
for .
Remark (1) (following in [12])
Let be a one dimensional fractional Brownian motion then
1) .
2) is a covariance function of fractional Brownian motion
such that
![]() | (1) |
3) If the covariance function becomes
min
.
Remark (2) (following in [19])
Let be a one dimensional fractional Brownian motion then for every
![]() |
1. If Then the increments of
are non-correlated, and consequently independent. So
is a Wiener Process which denoted further by
.
2. If then the increments are positively correlated.
3. If then the increments are negative correlated.
Definition (3) (following in [19])
A stochastic process is called
self similar if
and
have the same law.
Remark (3) (following in [19])
Fractional Brownian motion of Hurst index
is
self similar.
In the following sections, we explain the Integration of Deterministic Function with Respect to One Dimensional Fractional Brownian motion
Lemma (3) (following in [12])
The one dimensional fractional Brownian motion has the integral representation
![]() | (2) |
here, is a wiener process and the kernel
defined as
![]() | (3) |
![]() | (4) |
and
is a beta function.
Definition (4) (following in [19])
Let the general indicator function be given by
![]() |
The function f is said to be step function, if there exist a finite number of points
, and
, such that
.
Now, We denote by the set of step functions on . If
then by defined above we can write it by the form
, where
The integral of a step function with respect to one dimensional fractional Brownian motion is defined
, where
,
,
,
and
is a beta function.
Definition (5) (following in [19])
Let the general indicator function be given by
![]() |
The function f is said to be step function, if there exist a finite number of points
, and
such that
.
Now, We denote by the set of step functions on
If
then by defined above we can write it by the form
, where
.
The integral of a step function with respect to one dimensional fractional Brownian motion is defined
, where
.
Let be the Hilbert space defined as the closure of
with respect to the scalar product
.
The mapping can be extended to an isometry between
and
. i.e. the mapping
is isometry [22].
Remark (4) (following in [21])
• If and
then by using (Ito isometry theorem), we have
![]() | (5) |
• If from the equation ( 2.30), we have
![]() |
![]() | (6) |
![]() | (7) |
Lemma (4) (following in [11])
For any functions ,
, then
(i)
(ii)
![]() | (8) |
From this Lemma above, we obtain
![]() | (9) |
Remark (5) (following in [11])
The space contains the set of functions
such that
, which includes
.
Now, let be the Banach space of all measurable functions on
such that
![]() | (10) |
Lemma (5) (following in [18])
Let be the Banach space of all measurable functions on
and
be the Hilbert space defined as the closure of the set of step functions on
. If
then.
.
As for regard to Integration of Deterministic Function with Respect to Infinite Dimensional Fractional Brownian motion, Let and
be two real separable Hilbert spaces and Let
be the space of all bounded linear operators from
to
.
Definition (6) (following in [22])
A process with values in separable Hilbert space
is called Gaussian if, for every
and
the real random variable
has a normal distribution.
Definition (7) (following in [22])
The valued process
is said to be an infinite–dimensional fractional Brownian motion or (
fractional Brownian motion) if
is a centered Gaussian process with covariance COV
, where
the covariance operator.
Lemma (6) (following in [22])
is a
fractional Brownian motion if and only if there exists a sequence
of real and independent fractional Brownian motion such that
![]() |
where the series converges in and
the orthonormal system in Y.
Rmark (6) (following in [22])
Suppose that there exists a complete orthonormal system in
. Let
be the operator defined by
, where
are non-negative real numbers with finite trace
. The infinite dimensional fractional Brownian motion on Y can be defined by using covariance operator
as
, where
are one dimensional fractional Brownian motions mutually independent on
.
In order to defined stochastic integral with respect to the fractional Brownian motion. We introduce the space
of all
Hilbert-Schmidt operators that is with the inner product
is a separable Hilbert space.
Lemma (7) (following in [18])
Let be a family of deterministic functions with values in
The stochastic integral of
with respect to
is defined by
![]() | (1.14) |
Lemma (8) (following in [18])
If satisfies
then the above sum in lemma (1.13) is well defined as an
valued random variable and we have
![]() | (11) |
3. Problem Formulation
In this section, we study the existence and stability of inclusion equations, type of stochastic dynamical system driven by mixed fractional Brownian motion in a real separable Hilbert space of the following from:
![]() | (12) |
![]() |
Where is a generator of cosine semigroup on a Hilbert space
and
are
valued Brownian motion and fractional Brownian motion respectively.
To investigate the existence of the mixed-stochastic mild solution to the system (12), and for the operators A we make the following assumption :
1. A is the infinitesimal generator of a compact, analytic resolve operator in the Hilbert space
and there exists constant
and
such that
,
on
and
.
2. There exist constant such that
is a continuous function, satisfies the following Lipchitz condition, that is, for any
such that
![]() |
![]() |
3. a: ,
is a continuous function and there exists a constant
such that for all
![]() |
4.
5. For the initial condition there exists a positive constants and
such that
,
.
![]() |
6. The function satisfies For every
and there exists
such that
.
7. The multi-valued map is an
Caratheodory function satisfies the following conditions:-
i. For each the function
is u. s. c, and for each
the function
is measurable and for each fixed
the set
is nonempty.
ii. For each positive number there exists appositive function
independent on
such that
.
iii. .
8.
Where
![]() |
Lemma(9)
Let be a cosine semigroup and
-valued function
then the system (12) has a mixed–stochastic mild solution
![]() |
Proof:
![]() |
different both sides for S and use properties in Lemma (9), we get
![]() |
![]() |
Integrate both sides, we get
![]() |
![]() | (13) |
Definition (8)
A bounded function is called mixed solution of the inclusion system (12) if for any
![]() |
In this section, the existence of mixed-stochastic mild solution in to inclusion problem formulation (12) has been develop.
Theorem(1):
Suppose that conditions(1-8) are hold.
Then for initial value ,
, such that the intial value mixed-stochastic inclusion problem(1) has mixed-stochastic mild solution
.
Proof:
Let the operator defined by
![]() |
It is clear that the fixed points of are mild solutions of the system (12). Let
![]() | (14) |
![]() | (15) |
We prove that the operators and
are satisfy all the condition of theorem (1), Let
Step(1):- is a contraction
Let from assuming that
![]() |
![]() |
From the assumptions (1-4), we have
![]() |
By using initial condition (5), and taking supremum over for both sides, we get
![]() |
We can rewrite last inequality in the following from:
![]() |
Where
![]() |
Hence, we obtain
Step (2):- is convex for each
if
, then there exists
from condition
, we get
![]() | (16) |
![]() | (17) |
Let , then
![]() |
Since is convex (because
has convex values), then, we have
![]() |
Step (3):- maps bounded sets in to bounded sets in
. To show that there exists a positive constant
such that for each
we have
. If
then there exists
for each
, such that
![]() |
By using Lemma (1.8), Lemma (1.14) and by assumption (1), we obtain
![]() |
From assumptions (6) and (7-ii) ,we get
![]() | (18) |
Step(4):- maps bounded sets in to equicontinuous set of
, Let
such that
then for
and
then,there exists
such that for each
we have
![]() |
![]() |
![]() |
When the above inequality tends to zero, since S(t) in the uniform operator topology thus the set
is equicontinuous.
Step(5):- Now to prove is relatively compact in
for each
wehre
the set
is relatively compact in
for each
. Let
and
for
and
, there exists
such that
![]() | (19) |
Now, we define
![]() | (20) |
for each , thus,
![]() |
![]() |
Since sine simegroup operators are a continuous, we have
![]() |
Then, there exist , we get
![]() |
By using Lemmas (2), (8), and assumptions (1), (6), (7-ii), we obtain
![]() |
The relative compact sets arbitrarily close to the set then its relative compact in
thus
is a compact multi-valued closed graph .
Step (6):- Now to show that has a closed graph .
Let
and
we aim to show that
indeed,
means that there exists
![]() | (21) |
There exists , thus
![]() | (22) |
We must prove that there exists such that
![]() | (23) |
Suppose the liner continuous operator :
.
From lemma (1) it follows that is closed graph operator and we have
as
, thus
![]() |
Since it follows from Lemma (1) that,
![]() |
That is, there exists a such that
![]() |
Since be a linear continuous mapping from
to
in Lemma (1). Therefore
is a closed graph and
u.s.c.
Step (7):-The operator inclusion has a solution in
. Define an open ball B(0, r) in
, where
satisfies the inequality given in (20),we need to show that the system (12) has least one mild solution, for
for some
with
then, we have
![]() |
![]() |
By using assumptions (1-3)and (7-i) ,we get
![]() |
![]() |
From the assumptions(1),(2)and(3),(6) and using Lemmas (2) and (8), we obtain
![]() |
From assumption (6), we get
![]() | (24) |
![]() |
Thus
![]() |
Example (1)
Consider the following fractional differential equations
![]() |
![]() |
![]() |
![]() |
for ,
,where, where
are a constants.
(1) ,
(2) by
![]() |
(3) is generator of strongly cosine family
on
.
(4) The eigenvalues of is
and the eigenvectors
the set of function
is oryhonormal basis of
.
(5) For
also
for all
. In addition,
for
We assume
is
measurable satisfies
(6) The function is of classes
on
and
for each
(7) The function is continuous and there is
such that
(8) The function are continuous and there are appositive constants
such that
![]() |
(9) is a continuous function.
The following theorem investigate the stability of the inclution equation (12) by using Gron will Bellman inequality via cosine dynamical system.
We need to investigate the definition (8) on the inclusion problem (12).
Definition (9)
The solution of the system (12) in said to be stable , if for any
there exists a number
such that for any other solution
of the system (12) satisfying
then
is said to be asymptotically stable if it stable and if there is a constant
such that
then
![]() |
Theorem (2)
Assume the hypotheses (1-9) are hold, and has an asymptotically mild solution
Proof:
Let and
be a two solutions of equation (12) such that
![]() | (25) |
and
![]() | (26) |
Thus,
![]() |
Then,
![]() | (27) |
![]() |
Where .
References
[1] | Arnold L., “Stochastic Differential Equations; Theory and Applications”, John Wiley and Sons, 1974. | ||
![]() | |||
[2] | Balakrishnan A. V., “Applications of Mathematics: Applied Functional Analysis”, 3rd edition, Springer-Verlag, New York, 1976. | ||
![]() | |||
[3] | Bierens H. J., “Introduction to Hilbert Spaces”, Pennsylvania State University, June 24 2007. | ||
![]() | |||
[4] | Chen M., “Approximate Solutions of Operator Equations”, By World Scientific Publishing, Co. Pte. Ltd., 1997. | ||
![]() | |||
[5] | Coculescu D. and Nikeghbali A., “Filtrations”, 2000 Mathematics Subject Classification arXiv:0712.0622v1 [math.PR] , 2007. | ||
![]() | |||
[6] | Conway, John B., “A course in functional analysis”, 2' ed., Springer-Verlag, New York, 1990. | ||
![]() | |||
[7] | Diagana, T., “An Introduction to Classical and p-ADIC Theory of Linear Operators and Applications”, Nova Science Publishers, 2006. | ||
![]() | |||
[8] | Dhage. B.C.,Multi-valued mappings and fixed points II,Tamkang J.Math.37(2006). 27-46. | ||
![]() | |||
[9] | Erwin, K., “Introduction Functional Analysis with Application”, By John Wiley and Sons, 1978. | ||
![]() | |||
[10] | Einsiedler M. and Ward T., “Functional Analysis Notes”, Draft July 2, 2012. | ||
![]() | |||
[11] | Grippenberg, G. and Norros I., “On The Prediction of Fractional Brownian Motion”, Journal of Applied Probability, Vol. 33, No. 2, PP: 400-410, 1996. | ||
![]() | |||
[12] | Gani J., Heyde C.C., Jagers P. and Kurtz T.G., “Probability and its Applications”, Springer-Verlag London Limited, 2008. | ||
![]() | |||
[13] | Kumlin Peter, “A Note on Fixed Point Theory”, TMA 401 / MAN 670 Functional Analysis 2003 /2004. | ||
![]() | |||
[14] | KressRainer, “Linear Integral Equations”, 2’ed, Springer Science Business Media New York, 1999. | ||
![]() | |||
[15] | Kisil Vladimir. V “Introduction to Functional Analysis”, Courses on Functional Analysis at School of Mathematics of University of Leeds, December 2014 . | ||
![]() | |||
[16] | Kilbas, A.A., Srivastava, H.M., Trujillo, J.J. (2006). Theory and application of fractional differential Equations. Elsevier, Amsterdam. | ||
![]() | |||
[17] | Lasikcka, I., “Feedback semigroups and cosine operators for boundary feedback parabolic and hyperbolic equations”, J. Deferential Equation, 47, pp. 246-272, 1983. | ||
![]() | View Article | ||
[18] | Li K., “Stochastic Delay Fractional Evolution Equations Driven by Fractional Brownian Motion”, Mathematical Method in the Applied Sciences, 2014. | ||
![]() | |||
[19] | Mishura Y. S., “Stochastic Calculus for Fractional Brownian Motion and Related Processes”, Lect, Notes in Math., 1929, Springer, 2008. | ||
![]() | |||
[20] | Madsen Henrik, “ito integrals”, Aalborg university, Denmark, 2006. | ||
![]() | |||
[21] | Nualart D., “Fractional Brownian motion: stochastic calculus and Applications”, Proceedings of the International Congress of Mathematicians, Madrid, Spain, European Mathematical Society, 2006. | ||
![]() | View Article | ||
[22] | Tudor Ciprian A., “Ito Formula for the Infinite –Dimensional Fractional Brownian Motion”, J. Math. Kyoto Univ. (JMKYAZ), Vo. 45, No.3, PP: 531-546, 2005. | ||
![]() | |||