This document summarizes and reviews concepts related to Frechet derivatives. It begins by defining Frechet derivatives on Banach spaces and their properties such as differentiability of compositions of functions. It then discusses applications to ordinary differential equations, including the inverse function theorem. Higher order Frechet derivatives and partial derivatives on product spaces are also introduced. The document concludes by discussing concepts like the mean value theorem and Taylor's theorem in the context of Frechet derivatives.
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
Mathematics (from Greek μάθημα máthēma, “knowledge, study, learning”) is the study of topics such as quantity (numbers), structure, space, and change. There is a range of views among mathematicians and philosophers as to the exact scope and definition of mathematics
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Stochastic Calculus, Summer 2014, July 22,Lecture 7Con.docxdessiechisomjj4
Stochastic Calculus, Summer 2014, July 22,
Lecture 7
Connection of the Stochastic Calculus and Partial Differential
Equation
Reading for this lecture:
(1) [1] pp. 125-175
(2) [2] pp. 239-280
(3) Professor R. Kohn’s lecture notes PDE for Finance, in particular Lecture 1
http://www.math.nyu.edu/faculty/kohn/pde_finance.html
Today throughout the lecture we will be using the following lemma.
Lemma 1. Assume we are given a random variable X on (Ω, F, P) and a filtration
(Ft)t≥0. Then E(X|Ft) is a martingale with respect to filtration (Ft)t≥0.
Proof. The proof is very easy and follows from the tower property of the conditional
expectation. �
Corollary 2. Let Xt be a Markov process and Ft be the natural filtration asso-
ciated with this process. Then according to the above lemma for any function V
process E(V (XT )|Ft) is a martingale and applying Markov property we get that
E(V (XT )|Xt) is a martingale. In the following we often write E(V (XT )|Xt) as
EXt=xV (XT ).
As we will see this corollary together with Itô’s formula yield some powerful
results on the connection of partial differential equations and stochastic calculus.
Expected value of payoff V (XT ). Assume that Xt is a stochastic process satis-
fying the following stochastic differential equation
dXt = a(t, Xt)dt + σ(t, Xt)dBt, (1)
or in the integral form
Xt − X0 =
t
∫
0
a(s, Xs)ds +
t
∫
0
σ(s, Xs)dBs. (2)
Let
u(t, x) = EXt=xV (XT ) (3)
be the expected value of some payoff V at maturity T > t given that Xt = x. Then
u(t, x) solves
ut + a(t, x)ux +
1
2
(σ(t, x))2uxx = 0 for t < T, with u(T, x) = V (x). (4)
By Corollary 2 we conclude that u(t, x) defined by (3) is a martingale. Applying
Itô’s lemma we obtain
du(t, Xt) = utdt + uxdXt +
1
2
uxx(dXt)
2
= utdt + ux(adt + σdBt) +
1
2
uxxσ
2
dt
= (ut + aux +
1
2
σ
2
uxx)dt + σuxdBt, (5)
1this version July 21, 2014
1
2
Since u(t, x) is a martingale the drift term must be zero and thus u(t, x) solves
ut + aux +
1
2
σ
2
uxx = 0.
Substituting t = T is (3) we get that u(T, x) = EXT =x(V (XT )) = V (x).
Feynman-Kac formula. Suppose that we are interested in a suitably “discounted”
final-time payoff of the form
u(t, x) = EXt=x
(
e
−
T
∫
t
b(s,Xs)ds
V (XT )
)
(6)
for some specified function b(t, Xt). We will show that u then solves
ut + a(t, x)ux +
1
2
σ
2
uxx − b(t, x)u = 0 (7)
and final-time condition u(T, x) = V (x).
The fact that u(T, x) = V (x) is clear from the definition of function u. Therefore
let us concentrate on the proof of (7). Our strategy is to apply Corollary 2 and thus
we have to find some martingale involving u(t, x). For this reason let us consider
e
−
t
∫
0
b(s,Xs)ds
u(t, x) = e
−
t
∫
0
b(s,Xs)ds
EXt=x
(
e
−
T
∫
t
b(s,Xs)ds
V (XT )
)
= EXt=x
(
e
−
T
∫
0
b(s,Xs)ds
V (XT )
)
. (8)
According to Corollary 2
EXt=x
(
e
−
T
∫
0
b(s,Xs)ds
V (XT )
)
is a martingale and thus e
−
t
∫
0
b(s,Xs)ds
u(t, x) is a martingale. Applying Itô’s lemma
.
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On Frechet Derivatives with Application to the Inverse Function Theorem of Ordinary Differential Equations
1. www.ajms.com 1
ISSN 2581-3463
REVIEW ARTICLE
On Frechet Derivatives with Application to the Inverse Function Theorem of
Ordinary Differential Equations
Eziokwu C. Emmanuel
Department of Mathematics, Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria
Received: 25-10-2019; Revised: 15-11-2019; Accepted: 01-01-2020
ABSTRACT
In this paper, the Frechet differentiation of functions on Banach space was reviewed. We also investigated
that it is algebraic properties and its relation by applying the concept to the inverse function theorem of the
ordinary differential equations. To achieve the feat, some important results were considered which finally
concluded that the Frechet derivative can extensively be useful in the study of ordinary differential equations.
Key words: Banach space, Frechet differentiability, Lipschitz function, inverse function theorem
2010 Hematics Subject Classification: 46B25
INTRODUCTION
The Frechet derivative, a result in mathematical analysis, is derivative usually defined on Banach spaces.
It is often used to formalize the functional derivatives commonly used in physics, particularly quantum
field theory. The purpose of this work is to review some results obtained on the theory of the derivatives
and apply it to the inverse function theorem in ordinary differential equations.[1-5]
DERIVATIVES
Definition 1.1 (Kaplon [1958])
Let f be an operator mapping a Banach space X into a Banach space Y. If there exists a bounded linear
operator T from X into Y such that
( ) ( )
0 0
0
( )
lim 0
x
f x x f x T x
x
∆ →
+∆ − − ∆
=
∆
(1.1)
or,
( ) ( )
( )
0
lim x
t
f x th f x
T h
t
→
+ −
=
or
( ) ( )
0
T(y)
lim 0
y
f x y f x
y
→
+ − −
= (1.1)
then P is said to be Frechet differentiable at x0
, and the bounded linear operator
( )
,
0
P x T
= (1.2)
Address for correspondence:
Eziokwu C. Emmanuel
E-mail: okereemm@yahoo.com
2. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 2
is called the first Frechet – derivative of f at x0
. The limit in (1.1) is supposed to hold independent of the
way that x
∆ approaches 0. Moreover, the Frechet differential
( ) ( )
,
0 0
,
f x x f x x
∆
= ∆
is an arbitrary close approximation to the difference ( )
0 0
( )
f x x f x
+∆ − relative to x
∆ , for x
∆ small.
If f1
and f2
are differentiable at x0
, then
( ) ( ) ( ) ( )
1 2 0 1 0 2 0
f f x f x f x
′ ′ ′
+ = +
Moreover, if f2
is an operator from a Banach space X into a Banach space Z, and f1
is an operator from
Z into a Banach space Y, their composition 1 2
f f
is defined by
( )( ) ( )
( )
1 2 1 2 ,
f f x f f x for all x X
= ∈
We know that 1 2
f f
is differentiable at x0
if f2
is differentiable at x0
and f1
is differentiable at f2
(x0
) of
Z, with (chain rule):
( ) ( ) ( )
( )
1 2 1 2 0 2 0
( )
f f x f f x f x
′ ′ ′
=
To differentiate an operator f we write:
( ) ( ) ( ) ( )
0 0 0 0
, , ,
f x x f x T x x x x x
+ ∆ − = ∆ ∆ + ∆
where 0
( , )
T x x
∆ is a bounded linear operator for given 0,
x x
∆ with
0
0
lim ( , )
x
T x x T
∆ →
∆ =(1.3)
and
( )
0
0
,
lim 0
x
x x
x
∆ →
∆
=
∆
(1.4)
Estimate (1.3) and (1.4) give
0
0
lim ( , )
x
T x x f
∆ →
∆ =′
If 0
( , )
T x x
∆ is a continuous function of x
∆ in some ball ( )
0, ,( 0)
R R
∪ , then
( )
0 0
,0 ( )
T x f x
= ′
We now present the definition of a mosaic:
Higher – orderer derivatives can be defined by induction:
Definition 1.2 (Argyros [2005])
If f is (m – 1) – times Frechet – differentiable ( 2
m≥ an integer) and an m – linear operator A from X into
Y exists such that
( ) ( )
( 1) ( 1)
0 0
0
( )
lim 0
m m
x
f x x f x A x
x
− −
∆ →
+∆ − − ∆
=
∆
(1.5)
then A is called the m – Frechet – derivative of f at x0
, and
( )
0
( )
m
A f x
= (1.6)
3. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 3
Definition 1.3 (Koplan [1958])
Suppose f U R R
n m
: � � � �
⊆ → where U is an open set, the function f � is classically differentiable at x U
0 � �
∈ if
The partial derivatives of 0
, 1 1 ,
i
j
f
f fori mandj nexistsatx
x
∂
=
… =
…
∂
The Jacobean matrix ( ) ( ) x
0 0
m n
i
j
f
J x x R
x
∂
= ∈
∂
satisfies
( ) ( ) ( )( )
0
0 0
0
lim 0.
o
x x
f x f x J x x x
x x
→
− − −
=
−
We say that the Jacobean matrix J x
( )
0 is the derivative of 0
f at x that is called total derivative
Higher partial derivatives in product spaces can be defined as follows:
Define
( , )
ij j i
X T X X
= (1.7)
where X1
, X2
,… are Banach spaces and ( , )
j i
T X X is the space of bounded linear operators from X j into
Xi. The elements of Xij are denoted by ,
ij
T etc. Similarly,
1 2
( , ) ( , 1),
ijm m ij jk ij j
X T X X T X X jm
= = … − (1.8)
which denotes the space of bonded linear operators from X jm into 1 2 –1.
ij j
X jm
… The elements
1 2
ij j
A A jm
= … are a generalization of m – linear operators.
Consider an operator f1
from space
1
n
jp
p
X x
=
=∏ (1.9)
into Xi , and that fi has a partial derivative of orders 1,2, , – 1
m
… in some ball 0
( , )
x R
∪ , where 0
R and
( ) ( ) ( )
( )
0 0 0
0 1 2
, , ,
j j jn
x x x x X
= … ∈
For simplicity and without loss of generality, we (Frechet [1906]) remember the original spaces so that
1 2
1, 2, , n
j j j n
= = … =
hence, we write
( ) ( ) ( )
( )
0 0 0
0 1 2
, , , n
x x x x
= …
A partial derivative of ( –1)
order m of fi at 0
x is an operator
( 1)
0
1 2 1
1 2 1
( )
m
i
iq q qm
q q qm
f x
A
x x x
−
… −
−
∂
=
∂ ∂ …∂
(1.10)
1 2 1
( )
iq q qm
in X … − where
1 2 1
1 , , , m
q q q n
−
≤ … ≤
4. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 4
Let P Xqm
( ) denote the operator from Xqm into 1 2 1
iq q qm
X … − obtained by letting
(0)
,
j j m
x x j q
= ≠
for some ,1 .
m m
q q n
≤ ≤ Moreover, if
( )
( )
1
0
' 0 0
1 2 1 1
( ) ( )
. ,
m m
i i
qm
qm q q qm q qm
f x f x
P x
x x x x x x
−
−
∂ ∂ ∂
=
∂ ∂ ∂ …∂ ∂ …∂
(1.11)
exists, it will be called the partial Frechet – derivative of order ��m of fi with respect to 1 , ,
q qm
x x
… at x0
Furthermore, if fi is Frechet – differentiable m times at x0 , then
( )
0 0
1 1
1 1 2
( )
m m
i i
q qm s sm
q qm s q sm
f x f x
x x x x
x x x x x
∂ ∂
…
= …
∂ …∂ ∂ ∂ …∂
(1.12)
For any permutation 1 2
, , , m
s s s
… of integers 1 2
, , , m
q q q
… and any choice of point 1, , ,
q qm
x x
… from
1, ,
q qm
X X
… , respectively. Hence, if 1
( , , )
t
f f f
= … is an operator from 1 2 n
X X X X
= + +…+ into
1 2 t
Y Y Y Y
= + +…+ then
( )
0
( )
0
1
m
m i
j jm x x
f
f x
x x
=
∂
=
∂ …∂
(1.13)
1 2
1,2, , , , , , 1,2,
m
i t j j j n
= … … = … is called the –
m Frechet derivative of F� at 0
x = ( ) ( ) ( )
0 0 0
1 2
( , , , ) .
n
x x x
…
Integration[6]
In this subsection, we due to (Pantryagin [1962]) state results concerning the mean value theorem,
Taylor’s theorem and Riemannian integration without the proofs. Hence the mean value theorem for
differentiable real functions � f is stated as follows:
( ) – ( ) ’( ) ( – ),
f b f a f c b a
=
Where c ( , ),
a b
∈ does not hold in a Banach space setting. However, if F is a differentiable operator
between two Banach spaces and ,
X Y then
( )
( , )
( ) sup ( ) .
x L x y
f x f y f x x y
∈
− ≤ −
′
where
( ) ( )
{ }
, : 1 ,0 1
T x y z z y x
= = + − ≤ ≤
Set
( ) ( )
1 ,0 1,
y
z x
= + − ≤ ≤
Divide the interval 0 1
≤ ≤ into n subintervals of lengths , 1,2, , ,
i i n
∆ = … choose points i� inside
corresponding subintervals and as in the real Riemann integral consider sums
5. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 5
( ) ( )
1
n
i i i i
i
f f
=
∆
= ∆
∑ ∑
where is the partition of the interval, and set
( )
max i
i
= ∆
Definition 1.4 (Ince [1956])
If
( )
0
lim i i
S f
→
= ∆
∑
exists, then it is called the Riemann integral from f
( ) on [0,1], denoted by
( ) ( )
1
0
y
x
S f d f d
= =
∫ ∫
Definition 1.5[7]
A bounded operator ( )
P on [0,1] such that the set of points of discontinuity is of measure zero is said
to be integrable on [ , ].
0 1
Theorem 1.1 (Day [1973])
If F� is –
m times Frechet – differentiable in 0
( , ), 0
U x R R , and f x
m
( )
( ) is integrable from x to any
( )
0
U ,
x R
∈ then
( ) ( ) ( )
( )( ) ( )
1
1
1
, ,
!
m
n
n
m
n
f y f x f x y x R x y
n
−
=
= + − +
∑ (1.14)
( ) ( )
( )( )
( )
( )
( )
1
,
0
1
sup ,
! !
m
m
n
n m
x L x y
n
y x
f y f x y x f x
n m
−
∈
=
−
− − ≤
∑ (1.15)
where
( ) ( )
( )
( )
1
1
( )
0
1
, ( 1 ) ( )
1 !
m
m m
m
R x y f y x y x d
m
−
−
= + − −
−
∫ (1.16)
THEOREMS AND PROPERTIES[8,9]
Definition 2.1 (Arthanasius [1973])
Assume that X Y
,� are Banach spaces, S is an open subset of : ,
X and f S Y
→ is continuous and Frechet
differentiable at every point of S , Moreover, assume that for every 0
∈ there exists ∈
( ) 0 such that
(i) If 1 2 1 2
, , ( )
x x S with x x C
∈ − ≤ ∈ then ( ) ( )
'
1 2
[ ]
f x f x h h h X
− ≤∈ ∀ ∈
(ii) [ ]
( , )
x L h
∝ ≤∝ for every ( )
,
x S h X with h b
∈ ∈ ≤ ∈ then f is called C − differentiable on S
Theorem 2.1 (Arthanasius [1973])
Let f be a convex function defined on an open convex subset X of a Banach space X that is continuous
at .
x X
∈ Then, f is Frechet differentiable at xiff
�
( ) ( )
0
2 ( )
lim
t
f x th f x th f r
D
t
→
+ + − −
=
uniformly for x
h S
∈
6. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 6
Remark 2.1
Obviously, we have earlier seen that Frechet differentiability has additive property and the product of two
Frechet differentiable functions is Frechet differentiable function (the function that is Frechet differentiable
is continuous and therefore locally bounded). Now, we use boundedness of Frechet derivative and triangle
inequality. A function which is Frechet differentiable at a point is continuous there.
THE INVERSE FUNCTION THEOREM
An inverse function theorem is an important tool in the theory of differential equations. It ensures the
existence of the solution of the equation Tx y
=�� . Although T is not assumed to be compact and the
contraction principle might not be directly applicable, it is shown, in the proof of the inverse function
theorem, that the contraction principle can be used indirectly if �T has some appropriate differentiability
properties.
Definition 3.1 (Arthanasius [1973])
Let S be an open subset of the Banach space X � and let f map S
� � � into the Banach space �Y . Fix a point
0 0
and (
x S let f x
∈ ) 0, ,
x then f
= is said to be “locally invertible at ( )
0 0
,
x y if there exist two numbers
0, 0,
∝ with the following property: For every y 0 0
, ( )
S S y
∈ , there exists a unique ( )
0 0
x S x
∈ such
that ( ) .
f x y
=
Lemma 3.1 (uniqueness property of Frechet derivative) (Kaplan [1958])
Let LS Y
�� �
→ be given with S an open subset of the Banach space and
X Y another Banach space.
Suppose further that f is Frechet differentiable at x S
∈ . Then, the Frechet derivative of f at x
� � � is
unique.
Proof
Suppose that ( ) ( )
1 2
,
D x D x are Frechet derivatives of f at x
� � � with remainders ( ) ( )
1 1 2 2
, ,
x h x h
,
respectively. Then, we have
( ) ( ) ( )
1 1 2 2
, ( , )
D x h x h D x h x h
+ = +
for every 1 1
with .
h X x h S Here S
∈ + ∈ is some open subsets of S containing x. It follows that
( ) ( ) ( )
1 2 1 2
/ , ( , )
D x h D x h h x h w x h
− = − (3.1)
( ) ( )
1 2
1/ , , /
x h h x h h
≤ +
The last member of (3.1) tends to zero as 0.
h →
Let
( ) ( )
1 2 ,
x
T D x D x x x X
= − ∈
then T is a linear operator on X such that
0
lim / 0
x
Tx x
−
=
Consequently, given 0,
∈ there exists ( ) 0
∈ such that /
Tx x
for every
( ) ( )
with . with 0,let /2
x X x Given y X y x y y
∈ ∈ ∈ ≠ = ∈ .
Then ( ) or .
Tx
and Ty y Since
x
∞ ∈ n n is arbitrary, we obtain 0for every .
Ty y X
= ∈ We
conclude that ( ) ( )
1 2 .
D x D x
=
7. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 7
The existence of a bounded Frechet derivative f u
�� is equivalent to the continuity of .
f at x This is the
content of the next lemma.
Lemma 3.2 (Argyros [2005])
Let f S Y
: � �
→ be given where S is an open subset of a Banach space and
X Y Another Banach space,
Let � f be Frechet differentiable at x S
� ∈ . Then, f is continuous at x if ′( )
f x is a bounded linear
operator.
Proof
Let f be continuous at x S
�� ∈ . Then, for each 0
there exists ( ) ( )
0,1
∈ such that
( ) ( ) ( ) ( )
( ) /2, /2 /2
f x h f x f x h f x h h
+ − ∈ + −
for all ( )
with and .
h B x h S h
∈ + ∈ ∈
Therefore.
( ) ( ) ( )
'
/2 ( )
f x h h f x h f x
+ + −
For ( ), ,
h x h S
+ ∈ it follows that the linear operator ′
f x
( ) is continuous at the point 0 .
We should note here that the magnitude of the ball S plays no role in the Frechet differentiability of. This
meansthat,todefinetheFrechetderivative, ( ) of at ,
f x x
′ weonlyneedtohavethatcertaindifferentiability
conditions hold for all x h
+ � in a sufficiently small open neighborhood of the point
S x .
We now quote a well-known theorem of functional analysis the “bounded inverse theorem.”
Theorem 3.2 (Day [1973])
Let X Y
,� � be Banach spaces and let T X Y
: � �
→ be bounded linear, one-to-one and onto. Then, the inverse
1
of is a bounded linear operator on .
T T Y
−
We are ready for the inverse function theorem.
Theorem 3.3 (inverse function theorem) (Arthanasius [1973])
Let X Y
,� be Banach spaces and S an open subset of :
X Let f S Y
→ be C-differentiable on �S . Moreover,
assume that the Frechet derivative of the function is one-to-one and onto at some point , .
x S
∈ Then, the
function f � is locally invertible at the point ( )
( )
0 0
, .
x f x
Proof
Let ( )
0
D f x
= ′ . Then, the operator D−1
exists and is defined on 1
. Moreover
Y D−
is bounded. Thus, the
equation f x y
( ) = � is equivalent to the equation ( )
1 1
.
D f x D y fix y Y
− −
= ∈ and define the operator
on
U S as follows.
( )
1
,
x
U x D x f x x S
−
=
+ − ∈
(3.2)
obviously, the fixed points of the operator X � are solutions to the equation f x y
( ) =� � . We first determine
a closed ball inside S with center at x0 , on which X is a contraction operator. To this end fix
1
(0.1/ 4 )) and let ( ) 0 be such that
D
−
∈
8. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 8
( ) ( )
' '
0 2 1 2 1 2
( )
f x f x x x x x
− − ≤∈ − …
(3.3)
( )
2 1 2 1 2
,
x x x x x
− ≤ − … (3.4)
For every
( )
( )
1 2 1 0 2 0
, with / 2
2
x x S x x x x
∈ − ≤ − ≤
This is possible by virtue of the C-differentiability of the function � � f . Thus, we have
( )
1
1 2 1 2 1 2
( )
Xx Xx x x D f x f x
−
− = − − −
1 1 1
0 1 2 2 1 2 2 1 2
' ( ) ( ) '( )( ( )
D f x x x D f x x x D x x x
− − −
− − − −
( ) ( )
1 ' ' 1
0 2 1 2) 2, 1 2
( ( )
D f x f x x x D x x x
− −
≤ − − + −
1 1
1 2 1 2
D x x D x x
− −
≤ − + −
≤ ( ) −
1 2 1 2
/ x x
For every 1 2
,
x x S
∈ as above. It follows that X is a contraction operator on the ball S x
0 0
( ), where
1
( ) / 2 1/ (4 )
D
−
∝
= .
Now, we determine a constant 0 such that ( ) ( ) ( ) ( )
0 0 0 0 0 0
whenever
o o
XS x S x v S Y Here v f x
⊂ ∈ =
.in fact we have
1 1
0 0 0
( ) ( ) / 4
o
Xx Xx D y f x D y y
− −
− ≤ − = − ≤
whenever
1
( ) / (4
o
y y D
−
− ≤ =
n
Furthermore
0 0 0 0
X x Xx Xx Xx x
− = − + −
( )
1/ 2 , ( ) / 4 ( ) / 4 ( ) / 4 ( ) / 2
x x
≤ − + ≤ + =
For any 0 0
( )
x S x
∈ . We have shown that f is locally invertible at ( )
( )
0 0
, .
x f x and that for any ( )
0 ,
o
y S y
∈
there exists a unique ( ) ( ) .
o o
x S x With f x y
∈ =
Theorem 3.4 (Ince [1956])
Let the assumption of theorem 3.3 be satisfied with the C-differentiability of the function f replaced by
condition ( )
i of definition 3.1, then the conclusion of theorem 3.3 remains valid.
Example 3.1 (Leighton [1970]) let J a b
= [ ]
,� and let
, [ : ]
n
S x R x r
=
∈
9. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 9
( );
r
n
S x C J r
∞
= ∈ ∞
Where r is a positive number.
We consider a continuous function F J S R
o
n
: � �
× − and the operator '
1 ( )
n
X S C J
− defined as follows:
( )( ) ( )
( )
, , , '
Xx t F t x t t J S
= ∈ ∞∈
We first note that W is continuous on S� . In fact, since �F is uniformly continuous on the compact set
( )
for every 0 there exists 0
o
J S
× such that
( ) ( )
, ,
F t x f t y
−
For every x y So
,� �� ∈ with ( ) and every
x y t J
− . This implies that
Ux Uy
∞
−
Whenever,
'
, with , ( )
x y S x y
∞
∈ . To compute the Frechet derivative of X , we assume that the
Jacobean matrix
( )
1 , [( / )( , )] , 1,2
F t x F x t x i n
= ∂ ∂ = …
exists and is continuous on ,
J S
× . then given two function
( )
'1 1
0 1 0 0
0 , , such that '
n
x S r r h J x h C J x h S
∈ ∈ + ∈ + ∈ we have
( ) ( )
( ) ( )
( )
0 1
1
sup ( , , ( )
o
s
F t h t F t x t F t x t h t
∈
+ − −
( )
( ) ( )
( ) ( )
( )
0 1
1
sup{ [ / , , ] , ( )
o
s
F x F t x t h t F t x t h h
∞
∈
≤ ∂ − (3.5)
Where 1,2
n i n
= … are function of t lying in the interval ( , )
0 1 . In (3.5), we have used the mean value
theorem for real-valued functions on 0
S as follows:
( ) ( )
( ) ( )
( ) ( ) ( )
1 0 1 0 1 1 1
, , ( , 2
F t x t h t F t t F t z t h t i n
+ − ∞ = ∇ = …
Where ( ) ( ) ( )
1 0 1
z t x t h t
= + form the uniform continuity of ( ) ( )
1 1 1 1,
( , on
F t z t h t i i n J S
∇ = … × it
follows that the Frechet derivative 0
( )
X x exists and is a bounded linear operator given by the formula
( ) ( ) ( )( ) ( )( )
'
0 1 0
, 3.6
X x h t F t x t h t
=
REFERENCES
1. Argyros IK. Approximate Solution of Operator Equations with Application. World Scientific Pub. Co., Inc.; 2005.
p. 6-11.
2. Kartsatos AG. Advanced Ordinary Differential Equations. Tampa, USA: Mancorp Publishing; 1973.
3. Day MM. Normed Linear Spaces. 3rd
ed. New York: Springer; 1973.
4. Dunford N., Schwartz JT. Linear Operators, 3 Parts. New York: Inter-Science/Wiley; 1958.
10. Emmanuel: Frechet derivatives
AJMS/Jan-Mar-2020/Vol 4/Issue 1 10
5. Frechet M. Sur quelques points ducalcul functionel rend. Circ Mat Palermo 1906;22:1-74.
6. Ince E. Ordinary Differential Equations. New York: Dover; 1956.
7. Kaplan W. Ordinary Differential Equations. Boston, Massachusetts: Addision-Wesley; 1958.
8. Leighton W. Ordinary Differential Equations. 3rd
ed. Belmont, California: Wadsworth; 1970.
9. Pontryagin L. Ordinary Differential Equations. Boston, Massachusetts: Addison-Wesley; 1962.