Abstract
In this paper, we recall a more generalized integral transform, a generalized convolution product and a generalized first variation on function space. The Gaussian process and the bounded linear operators on function space are used to define them. We then establish the existence and various relationships between the generalized integral transform and the generalized convolution product. Furthermore, we obtain some relationships between the generalized integral transform and the generalized first variation with the generalized Cameron–Storvick theorem. Finally, some applications are demonstrated as examples.
Keywords:
generalized integral transform; generalized convolution product; bounded linear operator; Gaussian process; Cameron–Storvick theorem; translation theorem MSC:
47A60; 60J65; 28C20
1. Introduction
For , let be the one-parameter Wiener space and let denote the class of all Wiener measurable subsets of . Let m denote Wiener measure. Then, the space is complete, and we denote the Wiener integral of a Wiener integrable functional F by
Let be the space of all complex-valued continuous functions defined on which vanishes at and whose real and imaginary parts are elements of .
In [1], Lee studied an integral transform of analytic functionals on abstract Wiener spaces
For some parameters and and for certain classes of functionals, the Fourier–Wiener transform, the modified Fourier–Wiener transform, the analytic Fourier–Feynman transform and the Gauss transform are popular examples of the integral transform defined by (1) above (see [1,2,3,4,5,6,7,8,9,10,11,12]). Researchers have studied some theories of integral transform for functionals on function space. Recently, the integral transform is generalized by some methods in various papers. One of them uses the concept of Gaussian process instead of the ordinary process. For a function h on , the Gaussian process is defined by the formula
where the Paley–Wiener–Zygmund (PWZ) stochastic integral. Many mathematician use this process to generalize the integral. As representative examples, the generalized integral transforms
and
are studied in [13,14,15]. In fact, if and are identically 1 on , then Equations (2) and (3) reduce to Equation (1).
Another method is using the operators on K. Let S and R be bounded linear operators on K. In [6,16], the authors used this operators to generalize the integral transforms. A more generalized form is given by
If R is a constant operator and for some function h, then Equation (4) reduces to Equation (2), and hence it reduces to Equation (1) again. In previous studies, many relationships among the integral transform, the convolution and the first variation have been obtained. However, most of the results consist of fixed parameters.
In this paper, we use the both concepts, the Gaussian process and the operator, to define a more generalized integral transform, a generalized convolution product and a generalized first variation of functionals on function space. We then give some necessary and sufficiently conditions for holding some relationships between the generalized integral transforms and the generalized convolution products, and between the generalized integral transforms and the generalized first variations. In addition, some examples are given to illustrate usefulness for our formulas and results. By choosing the kernel functions and operators, all results and formulas in previous papers are corollaries of our results and formulas in this paper.
2. Definitions and Preliminaries
We first list some definitions and properties needed to understand this paper.
A subset B of is called scale-invariant measurable if is -measurable for all , and a scale-invariant measurable set N is called a scale-invariant null set provided for all . A property that holds except on a scale-invariant null set is said to hold scale-invariant almost everywhere (s-a.e.) [17]. For and , let denote the Paley–Wiener–Zygmund (PWZ) stochastic integral. Then, we have the following assertions.
- (i)
- For each , exists for a.e. .
- (ii)
- If is a function of bounded variation on , equals the Riemann–Stieltjes integral for s-a.e. .
- (iii)
- The PWZ stochastic integral has the expected linearity property.
- (iv)
- The PWZ stochastic integral is a Gaussian process with mean 0 and variance .
For a more detailed study of the PWZ stochastic integral, see [4,5,7,8,9,11,12,13,14,15,18].
Let
Then, is the Hilbert space with the inner product
where for . Furthermore, we note that and is one example of the abstract Wiener space [1,16,19,20]. For and with , is a well-defined Gaussian random variable with mean 0 and variance , where is the complex bilinear form on .
The following is a well-known integration formula which is used several times in this paper. For each with ,
For each , let
These functionals are called the exponential functionals on . It is a well-known fact that the class
is a fundamental set in . Thus, there is a countable dense which is dense in . Thus, we have that, for each ,
in the -sense, where is a sequence of constants.
Let be the class of all bounded linear operators on K. Then, for each and ,
where is the adjoint operator of S, see [16,19,21]. We state the conditions for the function h to obtain mathematically consistency as follows:
- (i)
- For each ,where for some because, although , may not be an element of for .
- (ii)
- LetThen, h is in (and hence ). However, may not be a Gaussian process. A condition for h is needed. Let h be an element of such that , where is the Lebesgue measure. Then, we have and is a Gaussian process.
- (iii)
- For each and , is stochastically continuous but it is not continuous, namely may not element of . However, if h is a function of bounded variation on , the Gaussian process is continuous and hence is well-defined for all . Since for with , , we have that
- (iv)
- Let
3. Generalization of the Integral Transform with Related Topics
We start this section by giving definition of generalized integral transform, generalized convolution product and the generalized first variation of functionals on K.
Definition 1.
Let be an element of and let F and G be functionals on K. Let . Then, the generalized integral transform of F, a generalized convolution product of F and G, and a generalized first variation of F with respect to and are defined by the formulas
and
for if they exist.
Remark 1.
- (1)
- When on , the generalized integral transform is the Fourier–Gauss transform [16].
- (2)
- When S and R are the constant operators, the generalized integral transform is a generalized integral transform used in [14,15]. In particular, if on , then is the integral transform used in [5,6,8,10,11,13,22].
- (3)
- When and on , is the convolution product used in [11].
We next state some notations used in this paper. For and , let
where for each . Furthermore, we have the symmetric property for .
In Theorem 1, we obtain the existence of generalized integral transform, generalized convolution product and generalized first variation of functionals in . In addition, we show that they are elements of .
Theorem 1.
Let be elements of and let . Let and be elements of and let . In addition, let for . Then, the generalized integral transform of , the generalized convolution product of and and the generalized first variation with respect to and exist, belong to and are given by the formulas
and
for .
4. Some Relationships with the Generalized Convolution Products.
In this section, we obtain some relationships between the generalized integral transform and the generalized convolution product of functionals in . In the first theorem in Section 4, we give a formula for the generalized integral transforms of functionals in . To establish some relationships, the following lemma is needed.
Lemma 1.
Let and let . Then, for each ,
Proof.
Using the following fact and Equation (12) repeatedly, we have
which complete the proof of Lemma 1. □
Theorem 2.
Let and be elements of and let and be elements of . In addition, let be an element of . Then,
for .
Proof.
From Theorem 1, we have
Applying Theorem 1 once more,
Finally, using Equation (16) in Lemma 1, we complete the proof of Theorem 2 as desired. □
Equations (18) and (19) in Theorem 3 are the commutative of the generalized integral transform and the Fubini theorem with respect to the generalized integral transform, respectively.
Theorem 3.
Let and be elements of and let and be elements of . In addition, let be an element of . Then,
if and only if
Furthermore,
if and only if
Proof.
From Theorems 2 and 3, we can establish the n-dimensional version for the generalized integral transform.
Corollary 1.
Let and be elements of and let be an element of . In addition, let be an element of . Then,
In our next theorem, we show that our generalized convolution product is commutative.
Theorem 4.
Let and D be elements of and let . Let and be elements of . Then,
if and only if
Proof.
The proof of Theorem 4 is a straightforward application of Theorem 1. □
In Theorem 5, we give a necessary and sufficient condition for holding a relationship between the generalized integral transform and the generalized convolution product.
Theorem 5.
For , let , and, for , let . In addition, for , let . Then,
if and only if the following equations hold
Proof.
To complete the proof of Theorem 5, we first calculate the left hand side of Equation (21). From Equation (14) in Theorem 1, we have
We next calculate the left hand side of Equation (21). From Equations (12) and (13) twice, we have
and
Hence, we complete the proof of Theorem 5 as desired. □
Corollary 2.
The following results and formulas stated bellow easily from Theorem 5.
- (1)
- Let S and R be elements of , and, for , let . In addition, for , let . Then,if and only if the following equations hold
- (2)
- For , let and . In addition, for , let . Then,if and only if the following equations hold
5. Some Relationships with the Generalized First Variations
In this section, we establish some formulas involving the generalized first variation. We next obtain a generalized Cameron–Storvick theorem for the generalized first variation and use this to apply for the generalized integral transform.
Theorem 6.
Let and . Let with . Then,
if and only if and , where .
Proof.
Hence, Equation (25) holds if and only if and
□
To establish a generalized Cameron–Storvick theorem for the generalized first variation, we need two lemmas with respect to the translation theorem on Wiener space.
Lemma 2.
(Translation Theorem 1) Let F be a integrable functional on and let . Then,
In [23], the authors used Equation (26) to establish Equation (28), which is a generalized translation theorem. The main key in their proof is the change of kernel for the Gaussian process, i.e.
where and for given .
The following lemma is said to be the translation theorem via the Gaussian process on Wiener space.
Lemma 3
(Translation Theorem 2). Let . Let and let be a integrable functional on . Let
Then,
In our next theorem, we establish the generalized Cameron–Storvick theorem for the generalized first variation.
Theorem 7.
Let be given. Let and . In addition, let and . Then,
Proof.
First, by using Equation (11) and the dominated convergence theorem, we have
We next apply the translation theorem to the functional instead of F in Lemma 2 to proceed the following formula
Since , we complete the proof of Theorem 7 as desired. □
In the last theorem in this paper, we use Equation (29) to give an integration formula involving the generalized first variation and the generalized integral transform. This formula tells us that we can calculate the Wiener integral of generalized first variation for generalized integral transform directly without calculations of them.
Theorem 8.
Let and let . In addition, let be as in Theorem 7. Then,
6. Application
We finish this paper by giving some examples to illustrate the usefulness of our results and formulas.
We first give a simple example used in the stack exchange and the signal process. For , let . Then, the adjoint is given by the formula .
Example 1.
Let and let and on . Then, . In addition, we have
This means that on and hence Thus, we obtain that
We give two examples in the quantum mechanics. To do this, we consider useful operators used in quantum mechanics. We consider two cases. However, various cases can be applied in appropriate methods as examples.
Case 1: Multiplication operator.
In the next examples, we consider the multiplication operator , which plays a role in physics (quantum theories) (see [21]). Before do this, we introduce some observations to proceed obtaining examples. Let such that
for all . In addition, for on , we define a multiplication operator by
Then, we have and Hence, Equation (31) holds. In addition, one can easily check that for all . Note that the expected value or corresponding mean value is
where x is the state function of a particle in quantum mechanics and is the probability that the particle will be found in .
In the first and second examples, we give some formula with respect to the multiplication operator .
Example 2.
Let and let and on . Then, . In addition, we have
and
This means that and on and hence Thus, we obtain that
Example 3.
Let and let and on . Then, . In addition, we have
and
This means that and on and hence
Thus, we obtain that
Case 2: Quantum mechanics operators.
In the next examples, we consider some linear operators which are used to explain the solution of the diffusion equation and the Schrôdinger equation (see [24]).
Let be the linear operator defined by
Then, the adjoint operator of S is given by the formula
and the linear operator is given by the formula
In addition, A is self-adjoint on and so
for all . Hence, A is a positive definite operator, i.e., for all . This means that the orthonormal eigenfunctions of A are given by
with corresponding eigenvalues given by
Furthermore, it can be shown that is a basis of and so is a basis of Ł2, and that A is a trace class operator and so S is a Hilbert–Schmidt operator on . In fact, the trace of A is given by . By using the concept of m-lifting on abstract Wiener space, the operators S and A can be extended on (see [19,25]).
We now give formulas with respect to the operators S and A, respectively.
Example 4.
This means that and on and hence Thus, we obtain that
Example 5.
Let and let and on . Then, . In addition, we have
and
This means that and on and hence Thus, we obtain that
We now give an example with respect to Theorem 8.
Example 6.
Let and , as used in the examples above. Let and let on . Furthermore, let on and let . Then, we have and on . Furthermore, we have
and
Hence, by using Equation (30) in Theorem 8, we can conclude that
7. Conclusions
In Section 3 and Section 4, we establish some fundamental formulas for the generalized integral transform, the generalized convolution product and the generalized first variation involving the generalized Cameron–Storvick theorem. As shown in Examples 2, 4 and 6, various applications are established by choosing the kernel functions and operators. The results and formulas are more generalized forms than those in previous papers. From these, we can conclude that various examples can also be explained very easily.
Funding
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2017R1E1A1A03070041).
Acknowledgments
The author would like to express gratitude to the referees for their valuable comments and suggestions, which have improved the original paper.
Conflicts of Interest
The author declares no conflict of interest.
References
- Lee, Y.J. Integral transforms of analytic functions on abstract Wiener spaces. J. Funct. Anal. 1982, 47, 153–164. [Google Scholar] [CrossRef]
- Cameron, R.H.; Martin, W.T. Transformations of Wiener integrals under translations. Ann. Math. 1944, 45, 386–396. [Google Scholar] [CrossRef]
- Cameron, R.H. Some examples of Fourier-Wiener transforms of analytic functionals. Duke Math. J. 1945, 12, 485–488. [Google Scholar] [CrossRef]
- Cameron, R.H.; Martin, W.T. Fourier-Wiener transforms of functionals belonging to L2 over the space C. Duke Math. J. 1947, 14, 99–107. [Google Scholar] [CrossRef]
- Chang, K.S.; Kim, B.S.; Yoo, I. Integral transforms and convolution of analytic functionals on abstract Wiener space. Numer. Funct. Anal. Optim. 2000, 21, 97–105. [Google Scholar]
- Ji, U.C.; Obata, N. Quantum white noise calculus. In Non-Commutativity, Infinite-Dimensionality and Probability at the Crossroads; QP-PQ: Quantum Probability and White Noise Analysis; World Scientific Publishing: River Edge, NJ, USA, 2002; Volume 16, pp. 143–191. [Google Scholar]
- Kim, B.J.; Kim, B.S.; Yoo, I. Integral transforms of functionals on a function space of two variables. J. Chungcheong Math. Soc. 2010, 23, 349–362. [Google Scholar]
- Kim, B.J.; Kim, B.S.; Skoug, D. Integral transforms, convolution products and first variations. Int. J. Math. Math. Soc. 2004, 11, 579–598. [Google Scholar]
- Kim, B.J.; Kim, B.S.; Skoug, D. Conditional integral transforms, conditional convolution products and first variations. Pan Amer. Math. J. 2004, 14, 27–47. [Google Scholar]
- Kim, B.J.; Kim, B.S. Parts formulas involving conditional integral transforms on function space. Korea J. Math. 2014, 22, 57–69. [Google Scholar] [CrossRef][Green Version]
- Kim, B.S.; Yoo, I. Generalized convolution product for integral transform on Wiener space. Turk. J. Math. 2017, 41, 940–955. [Google Scholar] [CrossRef]
- Kim, B.S.; Skoug, D. Integral transforms of functionals in L2(C0[0,T]). Rocky Mt. J. Math. 2003, 33, 1379–1393. [Google Scholar] [CrossRef]
- Chung, H.S.; Tuan, V.K. Generalized integral transforms and convolution products on function space. Integral Transform. Spec. Funct. 2011, 22, 573–586. [Google Scholar] [CrossRef]
- Lee, I.Y.; Chung, H.S.; Chang, S.J. Integration formulas for the conditional transform involving the first variation. Bull. Iran. Math. Soc. 2015, 41, 771–783. [Google Scholar]
- Lee, I.Y.; Chung, H.S.; Chang, S.J. Generalized conditional transform with respect to the Gaussian process on function space. Integ. Trans. Spec. Funct. 2015, 26, 925–938. [Google Scholar]
- Im, M.K.; Ji, U.C.; Park, Y.J. Relations among the first variation, the convolutions and the generalized Fourier-Gauss transforms. Bull. Korean Math. Soc. 2011, 48, 291–302. [Google Scholar]
- Johnson, G.W.; Skoug, D.L. Scale-invariant measurability in Wiener space. Pac. J. Math. 1979, 83, 157–176. [Google Scholar] [CrossRef][Green Version]
- Pierce, I.; Skoug, D. Integration formulas for functionals on the function space Ca,b[0,T] involving Paley-Wiener-Zygumund stochastic integrals. Pan Am. Math. J. 2008, 18, 101–112. [Google Scholar]
- Kuo, H.-H. Gaussian Measure in Banach Space; Lecture Notes in Mathematics; Springer: Berlin, Germany, 1975; Volume 463. [Google Scholar]
- Lee, Y.J. Unitary operators on the space of L2-functions over abstract Wiener spaces. Soochow J. Math. 1987, 13, 165–174. [Google Scholar]
- Kreyszig, E. Introductory Functional Analysis with Applications; John Wiley and Sons: Hoboken, NJ, USA, 1978. [Google Scholar]
- Chung, D.M.; Ji, U.C. Transforms on white noise functionals with their applications to Cauchy problems. Nagoya Math. J. 1997, 147, 1–23. [Google Scholar] [CrossRef]
- Chang, S.J.; Choi, J.G. A Cameron-Storvick theorem for the analytic Feynman integral associated with Gaussian paths on Wiener space and application. Comm. Pure Appl. Anal. 2018, 17, 2225–2238. [Google Scholar] [CrossRef]
- Chang, S.J.; Choi, J.G.; Chung, H.S. An approach to solution of the Schrôdinger equation using Fourier-type functionals. J. Korean Math. Soc. 2013, 53, 259–274. [Google Scholar] [CrossRef]
- Chang, S.J.; Choi, J.G. An analytic bilateral Laplace-Feynman transform on Hilbert space. Int. J. Math. 2014, 25, 1450118. [Google Scholar] [CrossRef]
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