2 The Khasminskii-type theorem for SFDEs with Markovian switching and jumps
Throughout this paper, unless otherwise specified, we use the following notations. Let
∣
x
∣
be the Euclidean norm of a vector
x
∈
R
n
. Let
R
+
be the family of nonnegative real numbers. If
A
is a matrix, its trace norm is denoted by
∣
A
∣
=
trace
(
A
T
A
)
. Let
τ
>
0
. Let
C
(
[
−
τ
,
0
]
;
R
n
)
be the family of continuous functions from
[
−
τ
,
0
]
to
R
n
with supremum norm
‖
φ
‖
=
sup
−
τ
≤
θ
≤
0
∣
φ
(
θ
)
∣
,
which is a Banach space. Let
(
Ω
,
ℱ
,
{
ℱ
t
}
t
≥
0
,
P
)
be a complete probability space with a filtration
{
ℱ
t
}
t
≥
0
satisfying the usual conditions (i.e., it is increasing and right continuous while
ℱ
0
contains all P-null sets). Let
p
≥
1
and
L
ℱ
t
p
(
[
−
τ
,
0
]
;
R
n
)
be the family of
ℱ
t
-measurable
C
(
[
−
τ
,
0
]
,
R
n
)
-valued random variables
ϕ
such that
E
‖
ϕ
‖
p
<
∞
. Let
W
(
t
)
=
(
W
1
(
t
)
,
…
,
W
m
(
t
)
)
T
be an m-dimensional Brownian motion defined on the probability space. Let
p
¯
=
{
p
¯
(
t
)
,
t
≥
0
}
be a stationary and
R
n
-valued Poisson point process. Then, for
A
∈
ℬ
(
R
n
−
{
0
}
)
, here
ℬ
(
R
n
−
{
0
}
)
denotes the Borel
σ
-field on
R
n
−
{
0
}
, and we define the Poisson counting measure
N
associated with
p
¯
by
N
(
(
0
,
t
]
×
A
)
=
∑
0
<
s
≤
t
I
A
(
p
¯
(
s
)
)
.
For simplicity, we denote
N
(
t
,
A
)
=
N
(
(
0
,
t
]
×
A
)
. It is well known that there exists a
σ
-finite measure
π
, such that
E
[
N
(
t
,
A
)
]
=
π
(
A
)
t
,
P
(
N
(
t
,
A
)
=
n
)
=
exp
(
−
π
(
A
)
t
)
(
π
(
A
)
t
)
n
n
!
.
This measure
π
is called the Lévy measure. Moreover, by Doob-Meyer’s decomposition theorem, there exists a unique
{
ℱ
t
}
t
≥
0
-adapted martingale
N
˜
(
t
,
A
)
and a unique
{
ℱ
t
}
t
≥
0
-adapted natural increasing process
N
ˆ
(
t
,
A
)
such that
N
(
t
,
A
)
=
N
˜
(
t
,
A
)
+
N
ˆ
(
t
,
A
)
,
t
>
0
.
Here,
N
˜
(
t
,
A
)
is called the compensated Lévy jumps and
N
ˆ
(
t
,
A
)
=
π
(
A
)
t
is called the compensator.
Let
r
(
t
)
,
t
≥
0
,
be a right-continuous Markovian chain on the probability space taking values in a finite state space
S
=
{
1
,
2
,
…
,
N
}
with generator
Γ
=
(
r
i
j
)
N
×
N
given by
P
{
r
(
t
+
Δ
)
=
j
∣
r
(
t
)
=
i
}
=
γ
i
j
Δ
+
o
(
Δ
)
,
if
i
≠
j
;
1
+
γ
i
j
Δ
+
o
(
Δ
)
,
if
i
=
j
.
Here,
Δ
>
0
and
γ
i
j
≥
0
,
i
≠
j
,
is the transition rate of the Markovian chain from
i
to
j
, while
γ
i
i
=
−
∑
i
≠
j
γ
i
j
. We assume that the Markovian chain, Brownian motion, and Lévy jumps are independent. For
Z
∈
ℬ
(
R
n
−
{
0
}
)
,
π
(
Z
)
<
∞
, consider a nonlinear neutral SFDE with Markovian switching and Lévy jump,
(1)
d
[
x
(
t
)
−
G
(
x
t
,
r
(
t
)
)
]
=
f
(
x
t
,
x
(
t
)
,
t
,
r
(
t
)
)
d
t
+
g
(
x
t
,
x
(
t
)
,
t
,
r
(
t
)
)
d
W
(
t
)
+
∫
Z
h
(
x
t
−
,
x
(
t
−
)
,
t
,
r
(
t
−
)
,
v
)
N
(
d
t
,
d
v
)
,
with the initial data
x
0
=
ξ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
. Here,
G
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
S
→
R
n
,
f
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
→
R
n
,
g
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
→
R
n
×
m
,
h
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
×
Z
→
R
n
, and for
θ
∈
[
−
τ
,
0
]
,
x
t
(
θ
)
=
x
(
t
+
θ
)
. Now we denote by
C
1
,
2
(
[
−
τ
,
∞
)
×
R
n
;
R
+
)
the family of all continuous nonnegative function
V
(
t
,
x
)
defined on
[
−
τ
,
∞
)
×
R
n
, such that they are continuously twice differentiable in
x
and once in
t
. Given
V
∈
C
1
,
2
(
[
−
τ
,
∞
)
×
R
n
;
R
+
)
, define the function
L
V
:
R
+
×
C
(
[
−
τ
,
0
]
;
R
n
)
→
R
by
L
V
(
t
,
φ
)
=
V
t
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
+
V
x
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
f
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
+
1
2
trace
[
g
T
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
V
x
x
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
g
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
]
+
∫
Z
[
V
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
+
h
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
,
v
)
)
−
V
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
]
π
(
d
v
)
,
where
V
t
(
t
,
x
)
=
∂
V
(
t
,
x
)
∂
t
,
V
x
(
t
,
x
)
=
∂
V
(
t
,
x
)
∂
x
1
,
…
,
∂
V
(
t
,
x
)
∂
x
n
,
V
x
x
(
t
,
x
)
=
∂
2
V
(
t
,
x
)
∂
x
i
∂
x
j
n
×
n
.
Assumption 2.1
(Local Lipschitz condition) For any integer
m
≥
1
, there exists a positive constant
k
m
, such that
∣
f
(
φ
,
x
,
t
,
i
)
−
f
(
ϕ
,
y
,
t
,
i
)
∣
2
∨
∣
g
(
φ
,
x
,
t
,
i
)
−
g
(
ϕ
,
y
,
t
,
i
)
∣
2
∨
∫
Z
∣
h
(
φ
,
x
,
t
,
i
,
v
)
−
h
(
ϕ
,
y
,
t
,
i
,
v
)
∣
2
π
(
d
v
)
≤
k
m
(
‖
φ
−
ϕ
‖
2
+
∣
x
−
y
∣
2
)
,
for any
φ
,
ϕ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
,
x
,
y
∈
R
n
with
‖
φ
‖
∨
‖
ϕ
‖
∨
∣
x
∣
∨
∣
y
∣
≤
m
,
i
∈
S
and any
t
∈
R
+
.
Assumption 2.2
(Contraction condition) For any
p
≥
1
, there exists a constant
κ
∈
(
0
,
1
∕
2
)
such that for all
φ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
,
i
∈
S
,
E
(
∣
G
(
φ
,
i
)
∣
p
)
≤
κ
p
sup
−
τ
≤
θ
≤
0
E
(
∣
φ
(
θ
)
∣
p
)
.
Assumption 2.3
(Khasminskii-type condition) Let
p
≥
1
.
There are two functions
V
∈
C
1
,
2
(
[
−
τ
,
∞
)
×
R
n
;
R
+
)
and
U
∈
C
(
[
−
τ
,
∞
)
×
R
n
;
R
+
)
, a probability measure
μ
(
⋅
)
on
[
−
τ
,
0
]
as well as a positive constant
K
, two positive constants
c
1
,
c
2
, such that for any
(
t
,
x
)
∈
R
+
×
R
n
,
(2)
c
1
∣
x
∣
p
≤
V
(
t
,
x
)
≤
c
2
∣
x
∣
p
,
and for any
(
t
,
φ
)
∈
R
+
×
C
(
[
−
τ
,
0
]
;
R
n
)
,
(3)
L
V
(
t
,
φ
)
≤
K
[
1
+
sup
−
τ
≤
θ
≤
0
V
(
t
+
θ
,
φ
(
θ
)
)
]
−
U
(
t
,
φ
(
0
)
)
+
∫
−
τ
0
U
(
t
+
θ
,
φ
(
θ
)
)
d
μ
(
θ
)
.
Assumption 2.4
For the function
V
stated in Assumption 2.3 and constant
K
, we have
∣
V
x
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
g
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
∣
≤
K
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
t
+
θ
,
φ
(
θ
)
)
)
,
∫
Z
[
V
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
+
h
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
,
v
)
)
−
V
(
t
,
φ
(
0
)
−
G
(
φ
,
r
(
t
)
)
)
]
2
π
(
d
v
)
≤
K
2
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
t
+
θ
,
φ
(
θ
)
)
)
2
for all
(
t
,
φ
)
∈
R
+
×
C
(
[
−
τ
,
0
]
;
R
n
)
.
Theorem 2.1
Under Assumptions
2.1–2.4, for any given initial data
x
0
=
ξ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
, there is a unique global solution
x
(
t
)
to equation (1) on
t
∈
[
−
τ
,
∞
)
. Moreover, for any
T
≥
0
, the solution has the property that
E
sup
−
τ
≤
t
≤
T
∣
V
(
t
,
x
(
t
)
)
∣
≤
C
4
e
C
3
T
,
where
C
1
=
E
V
(
0
,
x
(
0
)
−
G
(
ξ
,
r
(
0
)
)
)
+
∫
−
τ
0
U
(
s
,
x
(
s
)
)
d
s
,
C
2
=
2
E
‖
ξ
‖
p
+
2
p
C
1
c
1
+
1
−
2
p
κ
p
c
2
+
2
p
K
c
1
+
2
2
p
+
5
c
2
K
2
c
1
2
(
1
−
2
p
κ
p
)
T
,
C
3
=
2
p
k
c
1
+
2
2
p
+
5
K
2
c
2
2
c
1
2
(
1
−
2
p
κ
p
)
,
C
4
=
C
2
c
2
.
Proof
Similar to [16] Theorem 3.15, there is a unique maximal local solution
x
(
t
)
on
t
∈
[
−
τ
,
σ
)
, where
σ
is the explosion time. To show that
x
(
t
)
is actually global, we need to show
σ
=
∞
, a.s. Let
k
0
>
0
be sufficiently large for
‖
ξ
‖
<
k
0
. For each integer
k
≥
k
0
, define the stopping time
σ
k
=
inf
{
−
τ
≤
t
<
σ
:
∣
x
(
t
)
∣
≥
k
}
,
where, as usual,
inf
∅
=
∞
.
Clearly,
σ
k
is nondecreasing and
lim
k
→
∞
σ
k
=
σ
∞
≤
σ
.
This proof can be completed if
σ
∞
=
∞
a.s.. By the Itô formula ([17], Lemma 4.4.6),
(4)
V
(
t
,
x
(
t
)
−
G
(
x
t
,
r
(
t
)
)
)
=
V
(
0
,
x
(
0
)
−
G
(
x
0
,
r
(
0
)
)
)
+
∫
0
t
L
V
(
s
,
x
s
)
d
s
+
∫
0
t
[
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
]
d
W
(
s
)
+
∫
0
t
∫
Z
[
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
]
N
˜
(
d
s
,
d
v
)
.
By (3), we have
(5)
V
(
t
,
x
(
t
)
−
G
(
x
t
,
r
(
t
)
)
)
≤
V
(
0
,
x
(
0
)
−
G
(
x
0
,
r
(
0
)
)
)
+
K
∫
0
t
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
+
θ
,
x
(
s
+
θ
)
)
)
d
s
−
∫
0
t
U
(
s
,
x
(
s
)
)
d
+
∫
0
t
∫
−
τ
0
U
(
s
+
θ
,
x
(
s
+
θ
)
)
d
μ
(
θ
)
d
s
+
∫
0
t
[
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
]
d
W
(
s
)
+
∫
0
t
∫
Z
[
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
]
N
˜
(
d
s
,
d
v
)
.
By the Fubini theorem, we have
(6)
∫
0
t
∫
−
τ
0
U
(
s
+
θ
,
x
(
s
+
θ
)
)
d
μ
(
θ
)
d
s
=
∫
−
τ
0
∫
0
t
U
(
s
+
θ
,
x
(
s
+
θ
)
)
d
s
d
μ
(
θ
)
≤
∫
−
τ
0
∫
−
τ
t
U
(
s
,
x
(
s
)
)
d
s
d
μ
(
θ
)
≤
∫
−
τ
t
U
(
s
,
x
(
s
)
)
d
s
.
Substituting (6) into (5) yields
V
(
t
,
x
(
t
)
−
G
(
x
t
,
r
(
t
)
)
)
≤
C
¯
+
K
∫
0
t
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
+
θ
,
x
(
s
+
θ
)
)
)
d
s
+
∫
0
t
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
d
W
(
s
)
+
∫
0
t
∫
Z
[
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
]
N
˜
(
d
s
,
d
v
)
,
where
C
¯
=
V
(
0
,
x
(
0
)
−
G
(
x
0
,
r
(
0
)
)
)
+
∫
−
τ
0
U
(
s
,
x
(
s
)
)
d
s
. This implies that for any
k
≥
k
0
,
t
<
T
, where
T
is an arbitrary positive constant,
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
−
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
)
≤
C
¯
+
K
∫
0
t
∧
σ
k
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
+
θ
,
x
(
s
+
θ
)
)
)
d
s
+
∫
0
t
∧
σ
k
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
d
W
(
s
)
+
∫
0
t
∧
σ
k
∫
Z
[
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
]
N
˜
(
d
s
,
d
v
)
.
Taking upper bound and expectation on the above inequality, we obtain
(7)
E
sup
0
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
−
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
)
≤
C
¯
+
K
sup
0
≤
t
≤
T
∫
0
t
∧
σ
k
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
+
θ
,
x
(
s
+
θ
)
)
)
d
s
+
E
sup
0
≤
t
≤
T
∫
0
t
I
[
0
,
σ
k
]
(
s
)
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
d
W
(
s
)
+
E
sup
0
≤
t
≤
T
∫
0
t
I
[
0
,
σ
k
]
(
s
)
∫
Z
[
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
]
N
˜
(
d
s
,
d
v
)
.
By the Burkhölder-Davis-Gundy inequality ([5], Theorem 1.7.3) and Assumption 2.4,
(8)
E
sup
0
≤
t
≤
T
∫
0
t
I
[
0
,
σ
k
]
(
s
)
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
d
W
(
s
)
≤
32
E
∫
0
T
I
[
0
,
σ
k
]
(
s
)
∣
V
x
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
g
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
)
∣
2
d
s
1
2
≤
32
K
E
∫
0
T
[
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
∧
σ
k
+
θ
,
x
(
s
∧
σ
k
+
θ
)
)
]
2
d
s
1
2
≤
32
K
E
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
2
d
s
1
2
≤
32
K
E
[
1
+
sup
−
τ
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
d
s
1
2
≤
c
1
(
1
−
2
p
κ
p
)
2
p
+
1
c
2
E
(
1
+
sup
−
τ
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
)
+
2
p
+
4
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
d
s
.
By Assumption 2.4, similar to (8) and [5], Theorem 1.7.3,
(9)
E
sup
0
≤
t
≤
T
∫
0
t
I
[
0
,
σ
k
]
(
s
)
∫
Z
(
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
)
N
˜
(
d
s
,
d
v
)
≤
32
E
∫
0
T
I
[
0
,
σ
k
]
(
s
)
∫
Z
∣
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
+
h
(
x
s
,
x
(
s
)
,
s
,
r
(
s
)
,
v
)
)
−
V
(
s
,
x
(
s
)
−
G
(
x
s
,
r
(
s
)
)
)
∣
2
π
(
d
v
)
d
s
1
2
≤
32
K
E
∫
0
T
(
1
+
sup
−
τ
≤
θ
≤
0
V
(
s
∧
σ
k
+
θ
,
x
(
s
∧
σ
k
+
θ
)
)
2
)
d
s
1
2
≤
c
1
(
1
−
2
p
κ
p
)
2
p
+
1
c
2
E
(
1
+
sup
−
τ
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
)
+
2
p
+
4
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
d
s
.
Substituting (8) and (9) into (7),
(10)
E
sup
0
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
−
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
)
≤
C
1
+
K
+
2
p
+
5
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
d
s
+
c
1
(
1
−
2
p
κ
p
)
2
p
c
2
E
(
1
+
sup
−
τ
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
)
,
where
C
1
=
E
V
(
0
,
x
(
0
)
−
G
(
ξ
,
r
(
0
)
)
)
+
∫
−
τ
0
U
(
s
,
x
(
s
)
)
d
s
.
Recall elementary inequality
∣
a
+
b
∣
p
≤
2
p
−
1
(
∣
a
∣
p
+
∣
b
∣
p
)
for any
p
≥
1
,
a
∈
R
n
,
b
∈
R
n
, so
∣
a
∣
p
≥
1
2
p
−
1
∣
a
+
b
∣
p
−
∣
b
∣
p
. Note the relationship between sup and inf, so by Fatou’s lemma, (2), and Assumptions 2.2–2.3, we have
(11)
E
sup
0
≤
t
≤
T
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
−
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
)
≥
c
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
−
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
∣
p
≥
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
+
E
sup
0
≤
t
≤
T
−
∣
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
∣
p
=
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
E
inf
0
≤
t
≤
T
∣
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
∣
p
≥
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
inf
0
≤
t
≤
T
E
∣
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
∣
p
≥
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
sup
0
≤
t
≤
T
E
∣
G
(
x
t
∧
σ
k
,
r
(
t
∧
σ
k
)
)
∣
p
≥
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
κ
p
sup
0
≤
t
≤
T
sup
−
τ
≤
θ
≤
0
E
∣
x
(
t
∧
σ
k
+
θ
)
∣
p
≥
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
κ
p
E
sup
0
≤
t
≤
T
sup
−
τ
≤
θ
≤
0
∣
x
(
t
∧
σ
k
+
θ
)
∣
p
=
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
κ
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
,
and
(12)
E
∫
0
T
[
1
+
sup
−
τ
≤
t
≤
s
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
]
d
s
≤
E
∫
0
T
[
1
+
c
2
sup
−
τ
≤
t
≤
s
∣
x
(
t
∧
σ
k
)
∣
p
]
d
s
.
Substituting (11) and (12) into (10) gives
(13)
c
1
1
2
p
−
1
E
sup
0
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
−
κ
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
1
+
K
+
2
p
+
5
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
[
1
+
c
2
sup
−
τ
≤
t
≤
s
∣
x
(
t
∧
σ
k
)
∣
p
]
d
s
+
c
1
(
1
−
2
p
κ
p
)
2
p
c
2
+
c
1
1
2
p
−
κ
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
.
By (13), we have
(14)
c
1
1
2
p
−
1
−
κ
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
1
+
c
1
2
p
−
1
E
‖
ξ
‖
p
+
K
+
2
p
+
5
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
T
+
K
+
2
p
+
5
c
2
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
sup
−
τ
≤
t
≤
s
∣
x
(
t
∧
σ
k
)
∣
p
d
s
+
c
1
(
1
−
2
p
κ
p
)
2
p
c
2
+
c
1
1
2
p
−
κ
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
.
So,
c
1
2
p
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
1
+
c
1
2
p
−
1
E
‖
ξ
‖
p
+
K
+
2
p
+
5
c
2
K
2
c
1
(
1
−
2
p
κ
p
)
T
+
c
1
(
1
−
2
p
κ
p
)
2
p
c
2
+
K
+
2
p
+
5
c
2
2
K
2
c
1
(
1
−
2
p
κ
p
)
E
∫
0
T
sup
−
τ
≤
t
≤
s
∣
x
(
t
∧
σ
k
)
∣
p
d
s
.
That is,
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
2
+
C
3
∫
0
T
E
sup
−
τ
≤
t
≤
s
∣
x
(
t
∧
σ
k
)
∣
p
d
s
,
where
C
2
=
2
E
(
‖
ξ
‖
p
)
+
2
p
C
1
c
1
+
1
−
2
p
κ
p
c
2
+
2
p
K
c
1
+
2
2
p
+
5
c
2
K
2
c
1
2
(
1
−
2
p
κ
p
)
T
,
C
3
=
2
p
K
c
1
+
2
2
p
+
5
K
2
c
2
2
c
1
2
(
1
−
2
p
κ
p
)
.
By the Gronwall inequality ([18] Lemma 2), we therefore obtain
(15)
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
2
e
C
3
T
.
So
k
p
P
(
σ
k
≤
t
)
≤
E
∣
x
(
t
∧
σ
k
)
∣
p
≤
E
sup
−
τ
≤
t
≤
T
∣
x
(
t
∧
σ
k
)
∣
p
≤
C
2
e
C
3
T
.
Let
k
→
+
∞
, then
lim
k
→
+
∞
P
(
σ
k
≤
t
)
=
0
, and hence,
P
(
σ
∞
≤
t
)
=
0
and
P
(
σ
∞
>
t
)
=
1
. Since
T
≥
t
>
−
τ
and
T
is arbitrary, we must have that
σ
∞
=
∞
a.s. By (2) and (15), we have
(16)
E
sup
−
τ
≤
t
≤
T
∣
V
(
t
∧
σ
k
,
x
(
t
∧
σ
k
)
)
∣
≤
C
2
c
2
e
C
3
T
.
Letting
k
→
∞
in (16) yields
(17)
E
sup
−
τ
≤
t
≤
T
∣
V
(
t
,
x
(
t
)
)
∣
≤
C
2
c
2
e
C
3
T
.
The proof is therefore completed.□
Remark 2.1
From (15), we see that the
p
th moment will grow at most exponentially with exponent
C
3
. That is,
limsup
t
→
∞
1
t
log
E
∣
x
(
t
)
∣
p
≤
C
3
.
Here,
C
3
=
2
p
k
c
1
+
2
2
p
+
5
K
2
c
2
2
c
1
2
(
1
−
2
p
κ
p
)
.
The next theorem shows that the
p
th exponential estimations implies the almost surely asymptotic estimations, and we give an upper bound for the sample Lyapunov exponent.
Theorem 2.2
Under Assumptions
2.1–2.4, for any given initial data
x
0
=
ξ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
, we have
(18)
limsup
t
→
∞
1
t
log
∣
x
(
t
)
∣
≤
2
k
c
1
+
2
8
K
2
c
2
2
c
1
2
(
1
−
4
κ
2
)
a.s.
That is, the sample Lyapunov exponent of the solution should not be greater than
2
k
c
1
+
2
8
K
2
c
2
2
c
1
2
(
1
−
4
κ
2
)
.
Proof
For each
n
=
1
,
2
,
⋯
, it follows from (15) (taking
p
=
2
) that
E
sup
n
−
1
≤
t
≤
n
∣
x
(
t
)
∣
2
≤
β
n
e
γ
n
,
where
β
n
=
2
E
‖
ξ
‖
2
+
4
C
1
c
1
+
1
−
4
κ
2
c
2
+
4
K
c
1
+
2
9
c
2
K
2
c
1
2
(
1
−
4
κ
2
)
n
, and
γ
=
4
k
c
1
+
2
9
K
2
c
2
2
c
1
2
(
1
−
4
κ
2
)
. Hence, for any
ε
>
0
, by the Chebyshev inequality, it follows that
P
{
ω
:
sup
n
−
1
≤
t
≤
n
∣
x
(
t
)
∣
2
>
e
(
γ
+
ε
)
n
}
≤
β
n
e
−
ε
n
.
Since
∑
n
β
n
e
−
ε
n
≤
2
E
‖
ξ
‖
2
+
4
C
1
c
1
+
1
−
4
κ
2
c
2
+
4
K
c
1
+
2
9
c
2
K
2
c
1
2
(
1
−
4
κ
2
)
∑
n
n
e
−
ε
n
<
∞
, by the Borel-Cantelli Lemma, we deduce that there exists an integer
n
0
such that
sup
n
−
1
≤
t
≤
n
∣
x
(
t
)
∣
2
≤
e
(
γ
+
ε
)
n
,
a.s.
n
≥
n
0
.
Thus, for almost all
ω
∈
Ω
, if
n
−
1
≤
t
≤
n
and
n
≥
n
0
, then
(19)
1
t
log
∣
x
(
t
)
∣
=
1
2
t
log
∣
x
(
t
)
∣
2
≤
(
γ
+
ε
)
n
2
(
n
−
1
)
a.s
.
Taking the limsup in (19) leads to an almost surely exponential estimate, that is,
limsup
t
→
∞
1
t
log
∣
x
(
t
)
∣
≤
γ
+
ε
2
a.s.
The required assertion (18) follows because
ε
>
0
is arbitrary.□
3 Neutral SDDEs with variable delays
We now turn to considering neutral stochastic differential delay equations (SDDEs) with Markovian switching and Lévy jumps where the delays are time-dependent variables. That is, we consider the following equation.
(20)
d
[
x
(
t
)
−
G
¯
(
x
(
t
−
δ
(
t
)
)
,
r
(
t
)
)
]
=
f
¯
(
x
(
t
−
δ
(
t
)
)
,
x
(
t
)
,
t
,
r
(
t
)
)
d
t
+
g
¯
(
x
(
t
−
δ
(
t
)
)
,
x
(
t
)
,
t
,
r
(
t
)
)
d
W
(
t
)
+
∫
Z
h
¯
(
x
(
t
−
δ
(
t
)
−
)
,
x
(
t
−
)
,
t
,
r
(
t
−
)
,
v
)
N
(
d
t
,
d
v
)
,
on
t
≥
0
with the initial data
x
0
=
ξ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
, where
δ
:
R
+
→
[
0
,
τ
]
,
G
¯
:
R
n
×
S
→
R
n
,
f
¯
:
R
n
×
R
n
×
R
+
×
S
→
R
n
,
g
¯
:
R
n
×
R
n
×
R
+
×
S
→
R
n
×
m
, and
h
¯
:
R
n
×
R
n
×
R
+
×
S
×
Z
→
R
n
are all Borel measurable. [7,9] have established the Khasminskii-type theorems for SDDEs with constant delay. But these results could not be applied to the SDDEs where the delay is time-variable. If we define
f
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
→
R
n
,
g
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
→
R
n
×
m
,
h
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
R
n
×
R
+
×
S
×
Z
→
R
n
, and
G
:
C
(
[
−
τ
,
0
]
;
R
n
)
×
S
→
R
n
by
G
(
φ
,
r
(
t
)
)
=
G
¯
(
φ
(
−
δ
(
t
)
)
,
r
(
t
)
)
,
f
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
=
f
¯
(
φ
(
−
δ
(
t
)
)
,
φ
(
0
)
,
t
,
r
(
t
)
)
,
g
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
)
=
g
¯
(
φ
(
−
δ
(
t
)
)
,
φ
(
0
)
,
t
,
r
(
t
)
)
,
h
(
φ
,
φ
(
0
)
,
t
,
r
(
t
)
,
v
)
=
h
¯
(
φ
(
−
δ
(
t
)
)
,
φ
(
0
)
,
t
,
r
(
t
)
,
v
)
,
then we can apply the theory established in the previous sections to this neutral SDDE with Markovian switching. Let us proceed in this way to see what we can obtain. First, we can transfer Assumption 2.1 into the following one.
Assumption 3.1
For each integer
m
≥
1
, there is a positive constant
k
m
such that
(21)
∣
f
¯
(
y
,
x
,
t
,
i
)
−
f
¯
(
y
¯
,
x
¯
,
t
,
i
)
∣
2
∨
∣
g
¯
(
y
,
x
,
t
,
i
)
−
g
¯
(
y
¯
,
x
¯
,
t
,
i
)
∣
2
∨
∫
Z
∣
h
¯
(
y
,
x
,
t
,
i
,
v
)
−
h
¯
(
y
¯
,
x
¯
,
t
,
i
,
v
)
∣
2
π
(
d
v
)
≤
k
m
(
∣
y
−
y
¯
∣
2
+
∣
x
−
x
¯
∣
2
)
,
for those
y
,
x
,
y
¯
,
x
¯
∈
R
n
with
∣
y
∣
∨
∣
x
∣
∨
∣
y
¯
∣
∨
∣
x
¯
∣
≤
m
and any
t
∈
R
+
.
The following assumption is corresponding to Assumption 2.2.
Assumption 3.2
(Contraction condition) For any
p
≥
1
, there exists a constant
κ
∈
(
0
,
1
∕
2
)
such that for all
φ
∈
C
(
[
−
τ
,
0
]
;
R
n
)
,
i
∈
S
,
E
∣
G
¯
(
φ
(
−
δ
(
t
)
)
,
i
)
∣
p
≤
κ
p
[
E
∣
φ
(
0
)
∣
p
+
E
∣
φ
(
−
δ
(
t
)
)
∣
p
]
.
Comparing with Assumption 2.3, we can obtain the following. For
V
∈
C
1
,
2
(
[
−
τ
,
∞
)
×
R
n
;
R
+
)
, the operator
L
V
:
R
+
×
C
(
[
−
τ
,
0
]
;
R
n
)
⟶
R
takes the form as follows:
L
V
(
t
,
φ
)
=
ℒ
V
(
φ
(
−
δ
(
t
)
)
,
φ
(
0
)
,
t
,
r
(
t
)
)
,
where
ℒ
V
:
R
n
×
R
n
×
R
+
×
S
⟶
R
is defined by
ℒ
V
(
y
,
x
,
t
,
i
)
=
V
t
(
t
,
x
−
G
¯
(
y
,
i
)
)
+
V
x
(
t
,
x
−
G
¯
(
y
,
i
)
)
f
¯
(
y
,
x
,
t
,
i
)
+
1
2
trace
[
g
¯
(
y
,
x
,
t
,
i
)
T
V
x
x
(
t
,
x
−
G
¯
(
y
,
i
)
)
g
¯
(
y
,
x
,
t
,
i
)
]
+
∫
Z
[
V
(
t
,
x
−
G
¯
(
y
,
i
)
)
+
h
¯
(
y
,
x
,
t
,
i
,
v
)
−
V
(
t
,
x
−
G
¯
(
y
,
i
)
)
]
π
(
d
v
)
.
And clearly, (3) should become
(22)
L
V
(
t
,
φ
)
≤
K
[
1
+
V
(
t
,
φ
(
0
)
)
+
V
(
t
−
δ
(
t
)
,
φ
(
−
δ
(
t
)
)
)
]
−
U
(
t
,
φ
(
0
)
)
+
∫
−
τ
0
U
(
t
+
θ
,
φ
(
θ
)
)
d
μ
(
θ
)
,
with
∫
−
τ
0
U
(
t
+
θ
,
φ
(
θ
)
)
d
μ
(
θ
)
=
U
(
t
−
δ
(
t
)
,
φ
(
−
δ
(
t
)
)
)
.
This implies that
μ
(
⋅
)
should be a point probability measure at
−
δ
(
t