On the Regularization Method for Solving Ill-Posed Problems with Unbounded Operators

Abstract

Let be a linear, closed, and densely defined unbounded operator, where X and Y are Hilbert spaces. Assume that A is not boundedly invertible. Suppose the equation Au=f is solvable, and instead of knowing exactly f only know its approximation satisfies the condition: In this paper, we are interested a regularization method to solve the approximation solution of this equation. This approximation is a unique global minimizer of the functional , for any , defined as follows: . We also study the stability of this method when the regularization parameter is selected a priori and a posteriori. At the same time, we give an application of this method to the weak derivative operator equation in Hilbert space.

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Kinh, N. (2022) On the Regularization Method for Solving Ill-Posed Problems with Unbounded Operators. Open Journal of Optimization, 11, 7-14. doi: 10.4236/ojop.2022.112002.

1. Introduction

Let A : D ( A ) X Y be a linear, closed, densely defined unbounded operator, where X and Y are Hilbert spaces. Consider the equation

A u = f (1)

Problem-solving solution of Equation (1) is called ill-posed [1] if A is not boundedly invertible. This may happen if the null space N ( A ) = { u : A u = 0 } is not trivial, i.e. A is not injective, or if A is injective but A 1 is unbounded, i.e. the range of A, R ( A ) is not closed [2].

If A < , problem-solving stable solution of Equation (1) has been extensively studied in the literature in detail ( [2] [3] [4] [5] [6] and references therein).

If f δ , the noisy data, are given

f δ f δ (2)

is a stable approximation to the unique minimal norn solution to Equation (1) was constructed by several methods (variational regularization, quasi solution, iterative regularization, ... [2] [3] [4] [5] [6] and references therein).

If A is a linear, closed, densely defined unbounded operator, problem (1) has been some recent research [2] [7] [8] [9] [10] [11], however, there are still many open problems such as parameter choice rules of regularization method with the linear closed, densely defined unbounded operator A : D ( A ) X Y .

Our aim is to study problem-solving stable approximation solution of Equation (1) when operator A is a linear, closed, and densely defined from space Hilbert X into space Hilbert Y. We shall present the regularization method for solving the problem (1), we shall present a priori and a posteriori parameter choice rules of regularization; at the same time give an application to the weak derivative operator equation.

The paper structure consists of 3 sections: Section 1 the introduction briefly summarizes the recent research results and come up with the problem that needs to be studied; Section 2 presents some main results; Section 3 presents an application of this method.

2. Some Main Results

Lemma 1. [2] Let A : D ( A ) X Y be a linear, closed, densely defined operator, where X and Y are Hilbert spaces, then

1) the operators T = A A and Q = A A are densely defined, self-adjoint;

2) A is closed, densely defined and A = A ;

3) the operators A ˜ : = ( I X + A A ) 1 : X Y , A A ˜ : X Y are both defined on all of X and are bounded, σ ( A ˜ ) [ 0,1 ] . Also, A ˜ is self-adjoint;

4) the operator A ^ : = ( I Y + A A ) 1 : Y X is bounded and self-adjoint and A A ^ : Y X is bounded.

Lemma 2. Let A : D ( A ) X Y be a linear, closed, densely defined operator, where X and Y are Hilbert spaces. If f = A y , y N ( A ) then y is unique.

Proof. Suppose y 1 , and y 2 satisfy f = A y 1 , y 1 N ( A ) , and f = A y 2 , y 2 N ( A ) then A ( y 1 y 2 ) = 0 . Thus y 1 y 2 N ( A ) . There exits u N ( A ) such that y 1 y 2 = u imply y 1 y 2 , u = y 1 , u y 2 , u = 0 = u , u . Thus u = 0 , it follows that y 1 = y 2 .

Theorem 1. For any f Y , the problem

F ( u ) = A u f 2 + α u 2 min , α = const > 0, (3)

has a unique solution u α = A ( A A + α I Y ) 1 f , where I Y is the identity operator on Y.

Proof. Consider the equation

( A A + α I Y ) w α = f , α = const > 0 (4)

which is uniquely solvable w α = ( A A + α I Y ) 1 f (Lemma 1). Let u α = A w α then

A u α = A A ( A A + α I Y ) 1 f = ( A A + α I Y ) ( A A + α I Y ) 1 f α I Y ( A A + α I Y ) 1 f = f α w α ,

or

A u α f = α w α .

We have

F ( u + v ) = A u f 2 + α u 2 + A v 2 + α v 2 + 2 Re [ ( A u f , A v ) + α ( u , v ) ] , (5)

for any v D ( A ) . If u = u α , then

( A u α f , A v ) + α ( u α , v ) = α ( w α , A v ) + α ( u α , v ) = α ( A w α , v ) + α ( u α , v ) = 0. (6)

Thus Equation (6) implies

F ( u α + v ) = F ( u α ) + A v 2 + α v 2 F ( u α ) (7)

and F ( u α + v ) = F ( u α ) if and only if v = 0 , so u α is the unique minimier of F ( u ) .

Theorem 1 is proved.

Theorem 2. If f = A y , y N ( A ) then

lim α 0 u α y = 0 , u α = A ( A A + α I ) 1 f . (8)

Proof. It follows from Lemma 2, y is unique. Write Equation (4) as A ( A w α y ) = α w α . Apply A , which is possible because w α D ( A ) , we obtain

A A ( u α y ) = α u α . (9)

Multiply Equation (9) by u α y , we obtain

( A A ( u α y ) , u α y ) = α ( u α , u α y )

or

A ( u α y ) 2 = α ( u α 2 ( u α , y ) ) . (10)

Since α > 0 this implies

u α 2 ( u α , y ) ,

so

u α y , α > 0.

Therefore one may assume (taking a subsequence) that u α weakly converges to an element z, u n : = u α n z , as α n 0 .

It follows from Equation (10) that

lim n A ( u n y ) = 0, i . e . lim n A u n f = 0.

We shall prove that z = y .

Let γ run through the set such that { A A γ } is dense in N , where N : = N ( A ) . Note that N ( T ) = N ( A ) , where T = A A . Because of the formulas X = R ( T ) ¯ N ( T ) the { γ } = D ( T ) is dense in X, and the set { T γ } is dense in N .

Multiply the equation T ( u α y ) = α u α by γ and pass to the limit α 0 . We obtain

( z y , T γ ) = 0.

We have assume y N . If z N , then z y N and z y N , so z y = 0 .

One may always assume that z N because T u α = T u α ˜ , where u α ˜ is the orthogonal projection of u α onto N .

Thus, we have u n : = u α n z , u n y . Thus implies lim n u n y = 0 .

For convenience for the reader we prove this claim. Since u n : = u α n z , one gets y lim _ n u n . The inequality u n y implies lim ¯ n u n y . Therefore lim n u n = y . This and the weakly converge u n : = u α n z imply strong convergence

u n y 2 = u n 2 + y 2 2 Re ( u n y ) 0, as n .

Theorem 2 is proved.

Theorem 3. If f δ f δ , f = A y , y N ( A ) and

F δ ( u ) = A u f δ 2 + α u 2 = min , (11)

then there exists a unique global minimier u α , δ to (11) and lim δ 0 u δ y = 0 , where u δ : = u α ( δ ) , δ and α ( δ ) is properly chosen, in particular lim δ 0 α ( δ ) = 0 .

Proof. It follows from Lemma 2, y is unique. The existence and uniqueness of the minimizer u α , δ of F δ ( u ) follows from Theorem 1 and u α , δ = A ( Q + α I Y ) 1 f δ . We have

u α , δ y u α , δ u α + u α f .

By Theorem 2, u α f : = η ( α ) 0 , as α 0 .

Let us estimate

u α , δ u α = A ( Q + α I Y ) 1 ( f δ f ) δ A ( Q + α I Y ) 1 .

By the polar decomposition theorem [12], one has A = U Q 1 / 2 , where U is a partial isometry, so U 1 . One has,

A ( Q + α I Y ) 1 = U Q 1 / 2 ( Q + α I Y ) 1 Q 1 / 2 ( Q + α I Y ) 1 = max λ 0 c λ 1 / 2 λ + α = 1 2 α ,

where the spectral representation for Q was used.

Thus

u α , δ y δ 2 α + η ( α ) . (12)

For a fixed small δ > 0 , choose α = α ( δ ) which minimizes the right side of Equation (12). Then lim δ 0 α ( δ ) = 0 and lim δ 0 ( δ 2 α ( δ ) + η ( α ( δ ) ) ) = 0.

Theorem 3 is proved.

Remark 1. We can also choose α ( δ ) = c δ k , with any k < 2 and c = const > 0 . The constant c can be arbitrary.

We can also choose α ( δ ) by a descrepancy principle. For example, consider the equation for finding α ( δ ) :

A u α , δ f δ = c δ , c = const > 1.

We assume that f δ > c δ .

That is the content of the following theorem.

Theorem 4. The equation

A u α , δ f δ = c δ , c = const > 1 , f δ > c δ , (13)

has a unique solution α = α ( δ ) > 0 , lim δ 0 α ( δ ) = 0 , and if u δ : = u α ( δ ) , δ , then lim δ 0 u δ y = 0 .

Proof. Let us prove that Equation (13) has a unique root α ( δ ) > 0 , lim δ 0 α ( δ ) = 0 . Indeed, using the spectial theorem [12], one gets

A u α , δ f δ 2 = [ A A ( Q + α I ) ] 1 f δ 2 = 0 | s s + α 1 | 2 d ( E s , f δ , f δ ) = α 2 0 d ( E s , f δ , f δ ) ( s + α ) 2 : = g ( α , δ ) ,

where E s is the resolution of the identity of Q.

One has g ( , δ ) = f δ 2 > c 2 δ δ , and g ( + 0 , δ ) = P N f δ 2 , where P N is the orthoprojector onto the subspace N = N ( Q ) = N ( A ) = R ( A ) .

Since f R ( A ) and f δ f δ , it follows that P N f δ δ , so

g ( + 0, δ ) δ 2 . The function g ( α , δ ) for a fixed δ > 0 is a continuous strictly increasing function of α on [ 0, ) . Therefore there exists a unique α = α ( δ ) > 0 which solves Equation (13) if f δ > c δ and c > 1 . Clearly lim δ 0 α ( δ ) = 0 , because lim δ 0 c α ( δ ) = 0 and the relation lim δ 0 α 2 ( δ ) 0 d ( E s , f δ , f δ ) ( s + α ( δ ) ) 2 = 0 implies lim δ 0 α ( δ ) = 0 . The function α = α ( δ ) is a monotonically growing function of δ with α ( + 0 ) = 0 .

Let us prove that lim δ 0 u δ y = 0 , where u δ : = u α ( δ ) , δ , and α ( δ ) solves Equation (13). By the definition of u δ , we get

A u α f δ 2 + α ( δ ) u δ 2 A y f δ 2 + α ( δ ) y 2 = δ 2 + α ( δ ) y 2 .

Since A u α f δ 2 = c 2 δ 2 > δ 2 , it follows that u δ y . Thus u δ z , and, as in the proof of Theorem 2, we obtain z = y and lim δ 0 u δ y = 0 .

Theorem 4 is proved.

Remark 2. Theorems 1 - 4 are well known in the case of a bounded operator A.

If A is bounded, then a necessary condition for the minimum of the functional f ( u ) = A u f 2 + α u 2 is the equation

A A u + α u = A f . (14)

Hence in this case conditions are required f D ( A ) .

If A is unbounded, then f does not necessarily belong to D ( A ) , so Equation (14) may have no sence. Therefore, some changes in the usual theory are necessary. The changes are given in this paper. We prove, among other things, that for any f Y , in particular for f D ( A ) , the element u α = A ( A A + α I Y ) 1 f is well defined for any α = const > 0 , provided that A is a closed, linear, densely defined operator in Hilbert space (Theorem 1).

3. Applications

As a simple concrete example of this type of approximation, consider differentiation in H = L 2 [ 0 , 1 ] .

We define the operator A : D ( A ) H H as follows

A f = d f d x , f D ( A ) ,

with D ( A ) = { f H : f is absolutely continuous on [ 0,1 ] and f ( x ) H } .

Then D ( A ) is dense in H since it contains the complete orthonormal set { sin n π x } n = 1 .

Clearly, A is a linear operator.

We show that A is a closed operator in Hilbert space H. Indeed, for suppose { f n } D ( A ) and f n f and f n g , in each case the convergence being in the L 2 [ 0,1 ] norm. Since

f n ( x ) = f n ( 0 ) + 0 x f n ( t ) d t ,

we see that the sequence of constant functions { f n ( 0 ) } converges in L 2 [ 0,1 ] and hence the numerical sequence { f n ( 0 ) } converges to some real number C.

Now define h D ( A ) by h ( x ) = C + 0 x g ( t ) d t . Then, for any x [ 0,1 ] , we have by of the Cauchy-Schwarz inequality

| f n ( x ) h ( x ) | = | f n ( 0 ) C + 0 x ( f n ( t ) g ( t ) ) d t | | f n ( 0 ) C | + 0 x | f n ( t ) g ( t ) | d t | f n ( 0 ) C | + f n g

and hence f n h uniformly. Therefore, f = h D ( A ) and A f = f = h = g , verifying that the operator A is closed, linear, densely defined in L 2 [ 0,1 ] .

Let

D = { g D ( A ) : g ( 0 ) = g ( 1 ) = 0 } .

Then for f D ( A ) and g D , we have

A f , g = 0 1 f ( t ) g ( t ) d t = f ( t ) g ( t ) | 0 1 0 1 f ( t ) g ( t ) d t = f , g

Therefore D D ( A ) and A g = g , for g D .

On the other hand, if g D ( A ) , let g = A g . Then

A f , g = f , g

for all f D ( A ) . In particular, for f 1 , we find that 0 1 g ( t ) d t = 0 .

Now let

h ( t ) = 0 t g ( s ) d s .

Then h D and A h = g = A g and hence h g N ( A ) . Therefore, A f , h g = 0 , for all f D ( A ) . But R ( A ) contains all continuous function and hence g = h D .

We conclude that

D ( A ) = D , and A g = g .

According to Theorem 1, for any f Y = L 2 [ 0 , 1 ] , the problem

F ( u ) = A u f 2 + α u 2 min , α = const > 0,

has a unique solution u α = A ( A A + α I ) 1 f , where I is the identity operator on Y = L 2 [ 0,1 ] . f Y = L 2 [ 0 , 1 ] does not necessarily belong to D ( A ) .

It follows from Theorem 2, that if f = A y , y N ( A ) then

lim α 0 u α y = 0 , u α = A ( A A + α I ) 1 f .

It follows from Theorem 3, that if f δ f δ , f = A y , and

F δ ( u ) = A u f δ 2 + α u 2 = min , (15)

then there exists a unique global minimier u α , δ to Equation (15) and lim δ 0 u δ y = 0 , where u δ : = u α ( δ ) , δ and α ( δ ) is properly chosen, in particular lim δ 0 α ( δ ) = 0 .

It follows from Theorem 4, that the equation

A u α , δ f δ = c δ , c = const > 1 , f δ > c δ ,

has a unique solution α = α ( δ ) > 0 , lim δ 0 α ( δ ) = 0 , and if u δ : = u α ( δ ) , δ , then lim δ 0 u δ y = 0 .

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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