1. Introduction
The Fourier transform is a cornerstone of mathematical analysis, with broad applications in signal processing, physics, and engineering. While effective for stationary signals, many real-world signals are non-stationary, requiring time–frequency methods. The Gabor transform, or short-time Fourier transform (STFT), decomposes signals into time- and frequency-shifted windows. It finds applications in harmonic analysis, sampling theory, quantum mechanics, geophysics, medicine, and signal/image processing [
1,
2,
3,
4,
5,
6,
7,
8]. Its theory has also been studied in abstract settings, such as hypergroups [
9], locally compact Abelian/non-Abelian groups [
10,
11,
12], and Gelfand pairs [
13].
A natural generalization arises via Sturm–Liouville operators on
:
where
is a positive,
, and even function. We assume:
Under these conditions,
induces the Chébli–Trimèche hypergroup, with eigenfunctions acting as hypergroup characters. This allows harmonic analysis analogous to the classical case. Recent results include the generalized Fourier transform,
g-function [
14], transform ranges [
15,
16], uncertainty principles [
17,
18], maximal functions [
19], variation-diminishing kernels [
20], spectral theorems and convolution products [
21], Paley–Wiener theorems and transmutation operators [
22,
23], heat equation [
24], Delsarte’s formula [
25], and wavelet transforms [
26].
Within this framework, in this paper, we continue the study of the generalized Gabor transform (GGT) in the Chébli–Trimèche/hypergroup frame, initiated in [
27]. Our objectives are:
Establish inversion and Calderón-type formulas for the GGT;
Develop the reproducing kernel theory, including Moore–Penrose inverses, Tikhonov regularization, and extremal functions.
The theory of reproducing kernels, developed by Aronszajn [
28], extended by Schwartz [
29], and formalized by Saitoh [
30], is fundamental for these developments. In particular, for any even
and
, the extremal function
exists and is explicitly given by
with kernel
as defined in the main text. Here
denotes the generalized Paley–Wiener space given in Equation (
34).
The remainder of the paper is organized as follows. In
Section 2, we recall harmonic analysis results for the generalized canonical Fourier transform [
31]. In
Section 3, we revisit the GGT and present new results. In
Section 4, we develop the reproducing kernel theory for the GGT setting and discuss applications, including Tikhonov regularization and extremal functions.
2. Preliminaries
This section introduces the harmonic analysis associated with the Lions operator
. The main references are [
21,
23]. First let us fix some notations:
For , the conjugate exponent is .
,
, is the space of functions
f on
with
where
For
, this space is equipped with the scalar product
,
, is defined similarly with measure
where
is the Harish-Chandra function related to
[
21].
: Space of even, continuous, compactly supported functions.
: Space of bounded continuous functions on .
: Schwartz space of rapidly decreasing even functions.
Generalized Schwartz space
, with seminorms
where
.
: The group of real matrices with determinant one.
The Lions operator satisfies the following properties:
- 1.
For every
, the equation
admits a unique
solution
on
.
- 2.
For all , the function is analytic.
- 3.
- 4.
For every
,
and
,
Remark 1. - 1.
If , , then reduces to the Bessel operator, with - 2.
If , , , then reduces to the Jacobi operator, with where is the Gauss hypergeometric function.
2.1. Generalized Fourier Transform
For
, the Fourier transform associated with
is
with inverse
Definition 1. For and , the generalized translation operator iswhere is supported on . Then, we have the following results [
21,
23]:
- 1.
If , then and .
- 2.
If
,
, then
- 3.
If
, then
- 4.
For such that , then .
- 5.
If
, then
2.2. Generalized Canonical Fourier Transform
Let , with .
For
, the generalized canonical Fourier transform [
31] is
where
From (
3), we derive
Special cases: The generalized canonical Fourier transform recover the Fresnel transform for
,
; the fractional Fourier transform for
,
; and the generalized Fourier transform
for
. (For more details, see [
31].)
The differential operator
of the Sturm–Liouville type defined by
has the following properties:
and
are connected by
where
is defined by
.
The kernel
is the unique solution of
If
, then
We denoted by
the space of functions, with
where
Then we have:
Riemann–Lebesgue-type lemma: For every
, we have
and
Inversion-type formula: If
such that
, then
Parseval-type formulas:
- (a)
In particular, we have the following Plancherel-type formula:
- (b)
extends to an isometric isomorphism from
onto
. Moreover, for all
,
3. Generalized Gabor Transform (GGT)
This section is devoted to proving new results for the GGT. First, we begin by recalling the main results concerning this transform established in [
27]. We denoted by
,
, the space of functions
f on
satisfying
where
and
. Then the generalized convolution product is defined on
by
We have the following properties:
If
and
, then
is in
, with
If
, then
belongs to
if and only if
, such that
If
, then
The modulation of
by the real number
s is given by
Then
For
and
, we defined the generalized Gabor transform (GGT), by
where
is defined by
Proposition 1. For and , we have Proposition 2 (Plancherel-type formula)
. For , we have for every , As in the classical setting, the GGT preserves the orthogonality property. More precisely, we have the following result.
Corollary 1. For , we have for every Proposition 3. For , we have for every and A straightforward computation yields the following results.
Proposition 4. Let be a non-trivial function. Then
- 1.
For every , - 2.
is a reproducing kernel Hilbert space (RKHS) in with kernel
such that, for all , We are now ready to establish the following inversion formula for the GGT.
Theorem 1 (Inversion formula)
. For a nonzero function , we have for every such that where is defined by (16). In order to prove the last result, we require the following lemma.
Lemma 1 (
-Inversion formula)
. For a nonzero function , we have for every where the limit is in Proof. Let
u be in
. Then for every
,
Moreover, by (
13), we have
Then, since
it follows from (
5) that the function
is continuous on
, such that
For
, we derive by (
9),
Thus, using (
19) and (
20), we obtain
It follows that for every , the function belongs to and the function is in .
Then involving (
18) and (
19), we get
Thus, using this relation and (
16),
As
u is in
we have in
Hence, by (
22), we obtain in
,
as desired. □
Proof of Theorem 1. From (
23), we derive that for a.e.
,
Moreover, by (
3), (
18) and (
21), we have
For
, let
be the sequence defined by
which satisfies
and
Using the same arguments as in (
24), we obtain that the function
is integrable on
with respect to
Thus, by (
25), we derive that, for almost every
,
Hence, by (
7), we conclude that
which completes the proof. □
We conclude this subsection with the following result.
Theorem 2 (Calderón-type reproducing formula)
. For such that , we have for every and that the functionbelongs to and satisfieswhere The proof of the last theorem requires the following lemmas.
Lemma 2. If such that , then the functionsatisfies, for almost all ,and Proof. Involving Plancherel-type formula (
8) and (
14), we get
Moreover, using the assumption on the window function, we derive (
28). □
Lemma 3. If such that and , then the function given by (
26)
belongs to and satisfies Proof. By (
15),
can be written as
Thus by (
9)–(
11), we obtain
Moreover, since
, then
Hence, by (
9),
which implies that
On the other hand, let
in
. Then,
and by (
29),
By proceeding as above, Equation (
30) is equal to
Therefore, by (
7), Equation (
31) is equal to
Then
Since by (
7),
then by (
32) and (
33),
Hence □
Proof of Theorem 2. Moreover, from Lemma 2, we have for almost all
and
with
. Thus, by the dominated convergence theorem, we get (
27). □
4. Practical Real Inversion Formulas
The theory of reproducing kernels has found wide applications in inverse problems, integral transforms, integral equations, inversion of bounded linear operators, sampling theory, differential equations with variable coefficients, and function approximation. Notable contributions in this area have been made by Saitoh et al. [
30,
32,
33,
34,
35].
Before addressing applications to Tikhonov regularization, it is useful to examine Moore–Penrose generalized inverses through the framework of RKHS. This approach provides a natural and powerful tool for solving best approximation problems in Hilbert spaces.
Let
E be a set and
an RKHS on
E with kernel
K. Given a linear bounded operator
, where
H is a Hilbert space, the classical best mean-square approximation problem is to find, for a given
,
In infinite-dimensional spaces, this problem is non-trivial and naturally leads to the concept of the Moore–Penrose generalized inverse. Its study involves both the existence of extremal functions and their explicit representation.
Tikhonov regularization introduces a positive parameter
to ensure stability and uniqueness. Following Saitoh [
30,
32], one defines a modified inner product on
by
The resulting space
is itself a Hilbert space with reproducing kernel
given by
where
is the adjoint of
.
For every
, the Tikhonov regularized extremal problem
admits a unique solution
, called the extremal function. This function has the explicit representation
This formulation demonstrates how reproducing kernel theory systematically yields Moore–Penrose generalized inverses and provides a constructive approach to best approximation problems in infinite-dimensional Hilbert spaces. It forms the theoretical foundation for applications such as Tikhonov regularization in the context of generalized Gabor transforms and other integral transforms.
In this paragraph, we apply the theory of reproducing kernels, with particular emphasis on Tikhonov regularization, to construct practical approximate solutions for equations involving bounded linear operators associated with the GGT.
4.1. Reproducing Kernels
For
, we introduce the generalized Paley–Wiener space by
This type of space was first introduced by Paley and Wiener [
36], and then studied extensively by Slepian and Pollak [
37] in signal processing.
Lemma 4. - 1.
The generalized Paley–Wiener equipped with the following map defined as is an inner product space.
- 2.
The generalized Paley–Wiener equipped with the following map defined as is a normed space.
Proof. It is clear that
is a vector space. Moreover, in both statements, the difficulty is to demonstrate that we are dealing with a defined form, since the other axioms of product scalar and norm are satisfied. So, it suffices to prove that if
, then
. Indeed, if
, then
As
, then
Involving (
36) and (
37), we derive that
Using the fact that
is an isometric isomorphism from
onto
and (
9), we derive that
. □
Proposition 5. admits the following reproducing kernelsuch that - 1.
For every , ;
- 2.
For every and
Proof. For
,
belongs to
. Then
Moreover, from (
4),
, and
This shows that the function is in , for every .
On the other hand, by (
35) and (
38),
Using the fact that
, we obtain
□
Corollary 2. is embedded in .
4.2. Extremal Functions
For
and
, we introduce the partial GGT by
Proposition 6. If , then is a linear bounded operator from into , such that Proof. The proof follows from (
12) and (
15). □
For
,
,
and
, we introduce the inner product in
by
and its associated norm by
Remark 2. A straightforward computation gives that the norms and are equivalent.
Proposition 7. For , the generalized Paley–Wiener spacehas a reproducing kernel given bywhere is the adjoint of defined byMoreover, we have: - 1.
- 2.
- 3.
where is given by (39).
Proof. By Remark 2, Corollary 2, and Proposition 6, we derive that
,
is a continuous linear functional on
. Then, from [
30],
admits a reproducing kernel denoted by
and we have
Furthermore, the previous identity implies that
Hence, since
we obtain the desired result. □
Remark 3. Following the approach of Proposition 5, we show that We now present the main result of this subsection.
Theorem 3. Let , and . Then the following statements hold:
- 1.
For every , there exists a unique best approximate function in the sense that it minimizes Moreover, this extremal function admits the representation - 2.
The extremal function satisfies the estimate
Proof. The existence and uniqueness of
satisfying (
41) follow from [
32]. Moreover, it admits the representation
On the other hand, from Proposition 7,
as desired. □
Corollary 3. If and , then for all ,
- 1.
;
- 2.
;
- 3.
.
Proof. Let
f be in
. Then for all
,
On the other hand, by (
40) and (
43), we have
Then, from Proposition 7,
Finally, from Proposition 7 and (
43), we have
The proof is complete. □
Remark 4. If is an isometry, i.e., , then
- 1.
- 2.
;
- 3.
, where ;
- 4.
, where .
Proposition 8. Let .
- 1.
For every , the extremal function is represented by - 2.
If , then and converges uniformly as to f.
- 3.
Let and let such that . Then
Proof. From Theorem 3 and Remark 3, the infimum given by (
42) is attained by a unique function
, and it is represented by
where
is given in Remark 3. Moreover
This gives (
44). On the other hand, by (
44),
Since
and
and then we obtain the second result. Finally, by (
44), we have
Therefore
By the relation
, we get
Thus, by (
9) we derive
which gives the desired result. □
4.3. The Extremal Function Associated to the GGT
For
and
, we introduce the inner product for the space
by
and its associated norm by
By (
17), we have
Using arguments similar to those in Proposition 7, Theorem 3, and Corollary 3, we obtain the following proposition.
Proposition 9. Then the generalized Paley–Wiener space has the following reproducing kernelsuch that - 1.
where is the adjoint of defined by - 2.
- 3.
- 4.
where is given by (
39).
Theorem 4. Let . Then the following statements hold:
- 1.
For and , there exists a unique best approximate function in the sense that it minimizes Moreover, this extremal function admits the representation - 2.
For g and , such that , we have - 3.
For , we have and converges uniformly as to f.
- 4.
For , we have , for every .
- 5.
For , we have for every , - 6.
For , we have for every ,
5. Conclusions and Perspectives
In this paper, we have investigated several theoretical aspects of the generalized Gabor transform associated with a class of Sturm–Liouville operators in the framework of the Chébli–Trimèche hypergroup. In particular, we established inversion and Calderón-type formulas for this transform and studied some of its fundamental properties.
Furthermore, by applying the general theory of reproducing kernel Hilbert spaces, we analyzed approximation problems related to the generalized Gabor transform. Using the approach developed by Saitoh and others, we derived explicit representations of the extremal functions corresponding to certain regularized minimization problems. In this context, the Moore–Penrose generalized inverse and the Tikhonov regularization method were employed to obtain stable approximate solutions of bounded linear operator equations involving the generalized Gabor transform.
These results demonstrate that the theory of reproducing kernels provides a powerful and natural framework for the analysis of generalized integral transforms and related approximation problems.
As perspectives for future work, several directions may be explored. For instance, one may investigate further properties of the generalized Gabor transform in different functional spaces, such as weighted Sobolev or modulation-type spaces. Another possible direction is the study of uncertainty principles, sampling theorems, or frame properties associated with this transform. Moreover, applications of the generalized Gabor transform to inverse problems and signal analysis in non-Euclidean settings could provide interesting developments.
Author Contributions
Conceptualization, S.G.; Methodology, H.M.; Validation, S.G.; Formal analysis, H.M.; Investigation, H.M.; Writing—original draft, H.M.; Writing—review and editing, S.G.; Visualization, H.M.; Project administration, S.G.; Funding acquisition, S.G. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU261672].
Data Availability Statement
No new data were created or analyzed in this study.
Acknowledgments
The authors are deeply indebted to the referees for providing constructive comments and help in improving the contents of this article. The second author thanks Khalifa Trimèche and Saburou Saitoh for their help.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Bremaud, P. Mathematical Principles of Signal Processing, Fourier and Wavelet Analysis; Springer: New York, NY, USA, 2002. [Google Scholar]
- Gabor, D. Theory of communication. Part 1: The analysis of information. J. Inst. Electr. Eng. Part III Radio Commun. Eng. 1946, 93, 429–441. [Google Scholar] [CrossRef]
- Ghobber, S.; Omri, S. Time-frequency concentration of the windowed Hankel transform. Integral Transforms Spec. Funct. 2014, 25, 481–496. [Google Scholar] [CrossRef]
- Ghobber, S. Dunkl-Gabor transform and time-frequency concentration. Czechoslov. Math. J. 2015, 65, 255–270. [Google Scholar]
- Mejjaoli, H.; Sraieb, N. Uncertainty principles for the continuous Dunkl Gabor transform and the Dunkl continuous wavelet transform. Mediterr. J. Math. 2008, 5, 443–466. [Google Scholar] [CrossRef]
- Mejjaoli, H. k-Hankel Gabor transform on
d and its applications to the reproducing kernel theory. Complex Anal. Oper. Theory 2021, 15, 14. [Google Scholar]
- Sraeib, N. Uncertainty principles for the q-Bessel windowed transform and localization operators. J. Math. Sci. 2023, 271, 434–457. [Google Scholar] [CrossRef]
- Wilczok, E. New uncertainty principles for the continuous Gabor transform and the continuous Gabor transform. Doc. Math. J. 2000, 5, 201–226. [Google Scholar]
- Czaja, W.; Gigante, G. Continuous Gabor transform for strong hypergroups. J. Fourier Anal. Appl. 2003, 9, 321–339. [Google Scholar] [CrossRef]
- Farashahi, A.G. Continuous partial Gabor transform for semi-direct product of locally compact groups. Bull. Malaysian Math. Soc. 2015, 38, 779–803. [Google Scholar] [CrossRef]
- Farashahi, A.G.; Kamyabi-Gol, R. Continuous Gabor transform for a class of non-Abelian groups. Bull. Belg. Math. Soc. 2012, 19, 683–701. [Google Scholar] [CrossRef]
- Feichtinger, H.G.; Kozek, W.; Luef, F. Gabor analysis over finite abelian groups. Appl. Comput. Harmon. Anal. 2009, 26, 230–248. [Google Scholar] [CrossRef]
- Trimèche, K. Generalized Wavelets and Hypergroups; Gordon and Breach Science Publishers: Amsterdam, The Netherlands, 1997. [Google Scholar]
- Achour, A.; Trimèche, K. La g-fonction de Littlewood-Paley associée à un opérateur différentiel singulier sur (0, ∞). Ann. Inst. Fourier 1983, 33, 203–226. [Google Scholar] [CrossRef]
- Andersen, N. On the range of the Chébli-Trimèche transform. Mh. Math. 2005, 144, 193–201. [Google Scholar] [CrossRef]
- Bloom, W.R.; Xu, Z.F. Fourier transforms of Schwartz functions on Chébli-Trimèche hypergroups. Mh. Math. 1998, 125, 89–109. [Google Scholar] [CrossRef]
- Attour, L.B.; Trimèche, K. Uncertainty principle and (Lp, Lq) sufficient pairs on Chébli-Trimèche hypergroups. Integral Transform. Spec. Funct. 2005, 16, 625–637. [Google Scholar] [CrossRef]
- Trimèche, K. Cowling-Price and Hardy theorems on Chébli-Trimèche hypergroups. Glob. J. Pure Appl. Math. 2005, 1, 286–305. [Google Scholar]
- Bloom, W.R.; Xu, Z.F. The Hardy–Littlewood maximal function for Chébli–Trimèche hypergroups. In Applications of Hypergroups and Related Measure Algebras, Contemporary Mathematics; American Mathematical Society: Providence, RI, USA, 1993; pp. 45–70. [Google Scholar]
- Bouzeffour, F.; Dziri, M.; Fitouhi, A. Variation diminishing convolution kernels associated with second-order differential operators. Integral Transforms Spec. Funct. 2013, 24, 1012–1026. [Google Scholar] [CrossRef]
- Chébli, H. Opérateur de convolution généralisée et semi-groupe de convolution. In Théorie du Potentiel et Analyse Harmonique; Lecture Notes in Mathematics; Springer: Berlin/Heidelberg, Germany, 1974; Volume 404, pp. 35–59. [Google Scholar]
- Chébli, H. Sur un théorème de Paley-Wiener associé à la décomposition spectrale d’un opérateur de Sturm-Liouville sur (0, ∞). J. Funct. Anal. 1974, 17, 447–461. [Google Scholar] [CrossRef]
- Trimèche, K. Transformation intégrale de Weyl et théorème de Paley-Wiener associés à un opérateur différentiel singulier sur (0, ∞). J. Math. Pures Appl. 1981, 60, 51–98. [Google Scholar]
- Fitouhi, A. Heat polynomials for a singular differential operator on (0, ∞). Constr. Approx. 1989, 5, 241–270. [Google Scholar] [CrossRef]
- Trimèche, K. Convergence des series de Taylor generalisées au sens de Delsarte. C. R. Acad. Sci. Paris Sér. A 1975, 281, 1015–1017. [Google Scholar]
- Trimèche, K. Inversion of the Lions transmutation operators using generalized wavelets. Appl. Comput. Harmon. Anal. 1997, 4, 97–112. [Google Scholar] [CrossRef]
- Mejjaoli, H. Time-frequency analysis associated with the generalized Gabor transform and applications. Hacet. J. Math. Stat. 2025. advanced online publication. [Google Scholar] [CrossRef]
- Aronszajn, N. Theory of reproducing kernels. Trans. Amer. Math. Soc. 1950, 68, 337–404. [Google Scholar]
- Schwartz, L. Sous-espaces hilbertiens d’espaces vectoriels topologiques et noyaux associés (noyaux reproduisants). J. Anal. Math. 1964, 13, 115–256. [Google Scholar]
- Saitoh, S. Theory of Reproducing Kernels and Its Applications; Longman Scientific Technical: Harlow, UK, 1988. [Google Scholar]
- Mejjaoli, H.; Poria, A. The linear canonical transforms associated with the Dunkl-type operator and its applications. Integral Transforms Spec. Funct. 2025. published online. [Google Scholar] [CrossRef]
- Saitoh, S. Reproducing Kernels and Their Applications; Pitman Research Notes in Mathematics Series; Addison Wesley Longman: Harlow, UK, 1997. [Google Scholar]
- Castro, L.P.; Saitoh, S.; Sawano, Y.; Simões, A.M. General inhomogeneous discrete linear partial differential equations with constant coefficients on the whole spaces. Complex Anal. Oper. Theory 2012, 6, 307–324. [Google Scholar]
- Saitoh, S. Integral transforms in Hilbert spaces. Proc. Jpn. Acad. Ser. A Math. Sci. 1982, 58, 361–364. [Google Scholar]
- Saitoh, S. A general theory of integral transforms and its appliatns. Math. Vesnik 1985, 37, 121–133. [Google Scholar]
- Paley, R.E.A.C.; Wiener, N. Fourier Transforms in the Complex Plane; American Mathematical Society Colloquium Publications; American Mathematical Society: Providence, RI, USA, 1934; Volume 19. [Google Scholar]
- Slepian, D.; Pollak, H.O. Prolate spheroidal wave functions, Fourier analysis and uncertainty I. Bell System Tech. J. 1961, 40, 43–63. [Google Scholar]
| Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |