Abstract
In this paper, we first obtain the Fourier transforms of some finite bivariate orthogonal polynomials and then by using the Parseval identity, we introduce some new families of bivariate orthogonal functions.
1. Introduction
The integral transforms have wide applications in many branches of physics, engineering, mathematics and in other scientific disciplines. There are many applications of the integral transforms to differential, integral, and integro-differential equations, and in the theory of special functions. In particular, the integral transform technique can be applied to derive the solutions of integral equations of convolution type, integral equations, differential equations, or integro-differential equations. The literature in this subject is huge and includes many research papers and books. For more details regarding this subject, we refer the readers to [1,2,3,4,5,6,7]. Integral transforms are also used in the solutions of problems regarding mathematical modelling [8,9].
In this article, we focus on just Fourier transform which is an integral transform. The most important use of the Fourier transformation is to solve many of the partial differential equations of the mathematical physics, such as Laplace, Heat, and Wave equations. Some applications of the Fourier transform include vibration analysis, sound engineering, communication, data analysis, etc. [10,11,12,13,14]. The Fourier transform is also an important image processing tool, especially in transformation, representation, and encoding, smoothing and sharpening images [5]. By comparing with the signal process that uses one-dimensional Fourier transform in imaging analysis, two- or multi-dimensional Fourier transforms are being used. Fourier transform has been widely used in the fields of image analysis.
Consider the following differential equation
where are real parameters and n is a positive integer. According to [15], this equation has generally six sequences of orthogonal polynomial solutions. Three of them are Jacobi, Laguerre and Hermite infinitely orthogonal polynomials [16] and three other ones, which are denoted by , and , are finitely orthogonal with respect to the F sampling, inverse Gamma and T sampling distributions, respectively (see [17,18]).
The study of orthogonal polynomials and their transformations have been the subject of many papers during the last several years. The families of orthogonal polynomials which are mapped onto each other can be introduced by using the well-known Fourier transform or other integral transforms [19]. For example, Hermite functions are eigenfunctions of a Fourier transform (see [20,21,22,23]). Likewise, the Jacobi polynomials are mapped onto the continuous Hahn polynomials [20] and by the Fourier-Jacobi transform, Jacobi polynomials are mapped onto the Wilson polynomials [23]. In [24], new examples of orthogonal functions are obtained via Fourier transforms of the generalized Ultraspherical polynomials and the generalized Hermite polynomials. In [25], the Fourier transform of Routh-Romanovski polynomials is investigated. Furthermore, via the Fourier transforms of the finite classical orthogonal polynomials and , and two symmetric sequences of finite orthogonal polynomials, new families of orthogonal functions are introduced in [21,26].
Recently, in [27] some new families of orthogonal functions in two variables were introduced by using Fourier transforms of specific functions derived from two-variable polynomials defined in [28,29] and then using the Parseval identity their orthogonality relations have been obtained. Also, in [30] the authors have defined finite bivariate orthogonal polynomials by using a Koornwinder’s method [28].
Motivated by papers on Fourier transforms of univariate orthogonal polynomials mentioned above, a similar approach in those papers has been developed for two-dimensional Fourier transforms. This approach allows us to derive new families of bivariate orthogonal functions. Also, a similar approach can be applied for multivariate orthogonal polynomials and their properties can be investigated.
The aim of this paper is to obtain new families of bivariate orthogonal functions by two-dimensional Fourier transforms of bivariate finite orthogonal polynomials given in [30] by means of Koorwinder’s method. The rest of the article is organized as follows: In Section 2, we first remind three classes of finite univariate orthogonal polynomials in [18] and then present fifteen classes of finite bivariate orthogonal polynomials which are introduced in [30]. In Section 3, via Fourier transforms of finite bivariate orthogonal polynomials, we obtain new families of bivariate orthogonal functions and then compute their orthogonality relations via Parseval identity.
2. Preliminaries
In this section, we recall the classes of finite univariate and bivariate orthogonal polynomials introduced in [18,30], respectively. We first start with three classes of finite univariate orthogonal polynomials.
2.1. The Classes of Finite Univariate Orthogonal Polynomials
2.1.1. The First Class of Finite Classical Orthogonal Polynomials
Consider the equation
as a special case of (1). By means of the Frobenius method, an explicit polynomial solution for Equation (2) is obtained as [18]
The first class of finite classical orthogonal polynomials denoted by is orthogonal on with respect to the weight function if and only if and . Indeed, if we rewrite Equation (2) in self-adjoint forms as
where , then if we multiply the equations in (4) by and , respectively and subtract them, we arrive at
where . Since
then if , , , the left hand side of (5) tends to zero. Thus, it follows
To calculate the norm square value of the polynomials , if we write the Rodrigues representation of the polynomials given by [18]
in the norm square value, we have
then from integration by parts it follows
Since
we find that
where is the well-known Gamma function defined by [31]
Thus, the following corollary holds.
Corollary 1
(Orthogonality relation). ([18]) The following relation is satisfied
if and only if
2.1.2. The Second Class of Finite Classical Orthogonal Polynomials
Let consider the second order differential equation of the form
as a special case of (1). By the Frobenius method, an explicit polynomial solution for this equation is obtained as [18]
By means of similar calculations applied for the first class of finite classical orthogonal polynomials it is seen that these polynomials are orthogonal on with respect to the weight function if and only if [18]. In other words
2.1.3. The Third Class of Finite Classical Orthogonal Polynomials
The third class is defined by
and they are solutions of the differential equation
They are orthogonal on with respect to the weight function if and only if Indeed, the orthogonality relation is as follows [18]
2.2. The Classes of Finite Bivariate Orthogonal Polynomials
Recently, in [30], fifteen families of finite bivariate orthogonal polynomials have been introduced by using Koornwinder’s method [28], which are now listed as follows:
2.2.1. The First Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.2. The Second Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.3. The Third Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if . In other words, we have
for and .
2.2.4. The Fourth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.5. The Fifth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.6. The Sixth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.7. The Seventh Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
Here, using the orthogonality relation (7) for polynomial , the following orthogonality relation
is satisfied for , and .
2.2.8. The Eight Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if . In other words, we have
for and .
2.2.9. The Ninth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , . In other words, we have
for , and .
2.2.10. The Tenth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if . In other words, we have
for and
2.2.11. The Eleventh Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if and . In other words, we have
for , and .
2.2.12. The Twelfth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if . In other words, we have
for and
2.2.13. The Thirteenth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if . In other words, we have
for and .
2.2.14. The Fourteenth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if , and . In other words, we have
for , and
2.2.15. The Fifteenth Sequence
Finite orthogonal polynomials defined as
are orthogonal with respect to the weight function
on the domain
if and only if and . In other words, we have
for and
In the present paper, we first consider Fourier transforms of some specific functions in terms of finite bivariate orthogonal polynomials listed above except for tenth, eleventh and twelft polynomial sequences and then we introduce new families of bivariate orthogonal functions via Parseval identity.
3. Fourier Transforms for the Set of the Polynomials
The Fourier transform for a function of one variable is defined as [32]
and the corresponding Parseval identity is given by
for .
The Fourier transform for a function of two variables is in the form [1]
and the corresponding Parseval identity is given by
Now, let us obtain the Fourier transforms of finite bivariate orthogonal polynomials given in the previous section in order to define some new families of bivariate orthogonal functions using the Parseval identity.
3.1. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (12). By using appropriate substitutions , and , we get
If we apply (3), then
and we can conclude that
where
and
such that is a special case of the hypergeometric function given by [31]
in which , ; is the Pochhammer symbol. Also, from the definition of Gamma function, it can be verified that
Hence, from the Parseval identity (39) we obtain
Now by taking and in (42), if we use the orthogonality relation (13) in the left-hand side of (42), we obtain
Theorem 1.
The special function
has an orthogonality relation of form
for and Please note that the weight function of this orthogonality relation is positive for and
3.2. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (14). If we apply the Fourier transform to the function , under the subsitutions and respectively we get
from the relations (41) and definition of Beta function
the latter expression can be also expressed as
where
and
Hence, from the Parseval identity (39), we obtain
Now by taking and in (44), and we use the orthogonality relation (15) in the left-hand side of (44), we obtain
Theorem 2.
The special function
has an orthogonality relation of form
for and . Please note that the weight function of this orthogonality relation is positive for and .
3.3. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (16). By using appropriate substitutions, we derive the Fourier transform of the function given above by taking into account the relations (41) as
since
we can conclude that
where
and
where is a special case of the hypergeometric function. Hence, from the Parseval identity (39), we obtain
Now by taking in (47) and using the orthogonality relation (17) in the left-hand side of (47), we obtain
Theorem 3.
The special function
has an orthogonality relation of form
for and . Please note that the weight function is positive for .
3.4. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined by (18). If we apply similar calculations as in the first function family for finding the Fourier transform of the function given by (48), by considering the relations (41) and (46), we have
and we can conclude that
where
and
Hence, from the Parseval identity (39), we write
and thus, by using result (49) and definition (48), and then applying substitutions , we obtain
Now by taking and in the left hand side of (50), then according to the orthogonality relation (19), we obtain
Theorem 4.
The special function
has an orthogonality relation in form
for and Please note that the weight function is positive for and .
3.5. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (20). By using the substitutions , and , respectively, and applying the identities (41) and (46), we get
Therefore, we can conclude that
where
and
Hence, from the Parseval identity (39), we obtain
Now by taking and in (52) and using the orthogonality relation (21) in the left-hand side of (52), we obtain
Theorem 5.
The special function
has an orthogonality relation of form
for and . Please note that the weight function of the orthogonality relation is positive for and
3.6. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (22). If we apply the Fourier transform for the function given by (53), we get
by using the relations (41) and (46), we can conclude that
where
and
Hence, from the Parseval identity (39), we obtain
Now by taking and in (54) and then use the orthogonality relation (23) in the left-hand side of (54), we obtain
Theorem 6.
The special function
has an orthogonality relation in form
for and Please note that the weight function is positive for and .
3.7. Fourier Transform of the Polynomials
Let us define
where are real parameters. Similar to the results in the paper [21], we get
where
and
Hence, from the Parseval identity (39) and then using the orthogonality relation of given by (24), after the necessary arrangements, we can give the next theorem:
Theorem 7.
The special function
has an orthogonality relation of form
where and Please note that the weight function of this orthogonality relation is positive for , , or , , ,
3.8. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials are defined in (26). As a result of the calculations in the paper [21], we get
where
and
By using the Parseval’s identity (39) and the orthogonality relation (27) for the polynomials, we can give next result.
Theorem 8.
The special function
has an orthogonality relation as follow
where and Please note that the weight function of this orthogonality relation is positive for and
3.9. Fourier Transform of the Polynomials
Let us define
where and are real parameters, the polynomials are defined by (28). In view of the calculations in the paper [21], we get
where
and
Theorem 9.
The special function
has an orthogonality relation of form
for and Please note that the weight function of this orthogonality relation is positive for , , or , ,
3.10. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials is defined in (33). Applying the Fourier transform for the function given in (58), we get
On the other hand, for
where the relations (41) and
are used. Also, for . Thus, from the relations (60) and (62),
and similarly the integral is calculated as
Now, substituting the calculated integrals and in (59) we get
where
and
where is the special case of the hypergeometric function. If the results are replaced in the Parseval identity (39), we obtain
Now by taking and in the left-hand side of the above equality and applying the orthogonality relation (34), it can be written that
in view of the relation
Theorem 10.
The special function
has an orthogonality relation of form
for and
3.11. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials is defined in (35). By applying similar calculations in the paper [21] and in the previous subsection, we get
where
and
Hence, from the Parseval identity (39), we obtain
Now by taking , and in the left-hand side of (66) and then using the orthogonality relation (36), in view of the relation (64), we obtain
Theorem 11.
The special function
has an orthogonality relation in form
for and . Please note that the weight function is positive for and or and
3.12. Fourier Transform of the Polynomials
Let us define
where and are real parameters, and the polynomials is defined by (37). In view of the calculations in the paper [21] and in similar calculations given for , we get
where
and
Hence, from the Parseval identity (39), we obtain
Now by taking and in the left-hand side of (68), then using the orthogonality relation (38) we have
in view of the relation (64).
Theorem 12.
The special function
has an orthogonality relation of form
for and . Please note that the weight function of the orthogonality relation is positive for
4. Conclusions
The integral transforms have many applications in mathematics, physics, engineering, and in other scientific disciplines. The most important use of the Fourier transformation is to solve differential equations, integral equations and partial differential equations of the mathematical physics such as Laplace, Heat, Wave equations. Some other applications of the Fourier transform include vibration analysis, sound engineering, communication, data analysis, etc. [10,11,12,13,14]. The Fourier transform is also an important image processing tool, especially in transformation, representation, and encoding, smoothing, and sharpening images [5]. Another use of the Fourier transform is that it allows us to derive new families of functions by means of Parseval identity. During the last several years, there were many papers on the study of orthogonal polynomials and their transformations. The families of orthogonal polynomials which are mapped onto each other can be introduced by using the well-known Fourier transform or other integral transforms. Up to now, Fourier transforms of Jacobi, generalized Ultraspherical, generalized Hermite, Routh-Romanovski polynomials, finite classical orthogonal polynomials, etc. and relations with other polynomials have been studied by many authors. By the motivation of Fourier transforms of orthogonal polynomials mentioned above, a similar method in those papers has been developed for two-dimensional Fourier transforms. This paper first deals with two-dimensional Fourier transforms of some specific functions in terms of finite bivariate orthogonal polynomials. Then, via Fourier transforms of finite bivariate orthogonal polynomials and Parseval identity, the new families of bivariate orthogonal functions have been derived. This study will be a material for researchers who study on orthogonal polynomials and special functions. The method applied for bivariate case in this paper can be applied for some other orthogonal polynomials in multivariate case. Furthermore, it is possible to investigate some partial differential operators whose eigenfunctions are the obtained new orthogonal functions and some their characteristic properties in further research.
Author Contributions
Investigation E.G.L., R.A. and M.M.-J.; writing-original draft E.G.L. and R.A.; writing-review and editing E.G.L., R.A. and M.M.-J. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not Applicable.
Informed Consent Statement
Not Applicable.
Data Availability Statement
Not Applicable.
Acknowledgments
The research of the first and second authors has been supported by Ankara University Scientific Research Project Unit (BAP) Project No:20L0430007. The work of the third author has been supported by the Alexander von Humboldt Foundation under the Grant number: Ref 3.4-IRN-1128637-GF-E.
Conflicts of Interest
The authors declare no conflict of interest.
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