Kernel Theorems in Coorbit Theory
Peter Balazs, Karlheinz Gr\"ochenig, Michael Speckbacher

TL;DR
This paper establishes general kernel theorems for operators between coorbit spaces, unifying and extending previous results for various function spaces like modulation and Besov spaces.
Contribution
It provides a unified framework for kernel theorems in coorbit theory, encompassing known results and introducing new theorems for Besov spaces.
Findings
Unified kernel theorems for coorbit spaces
Recovery of Feichtinger's kernel theorem as a special case
New kernel theorem for Besov space operators
Abstract
We prove general kernel theorems for operators acting between coorbit spaces. These are Banach spaces associated to an integrable representation of a locally compact group and contain most of the usual function spaces (Besov spaces, modulation spaces, etc.). A kernel theorem describes the form of every bounded operator between a coorbit space of test functions and distributions by means of a kernel in a coorbit space associated to the tensor product representation. As special cases we recover Feichtinger's kernel theorem for modulation spaces and the recent generalizations by Cordero and Nicola. We also obtain a kernel theorem for operators between the Besov spaces and .
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Kernel Theorems in Coorbit Theory
Peter Balazs
Acoustics Research Institute
Austrian Academy of Sciences
Wohllebengasse 12-14, 1040 Vienna
Austria
,
Karlheinz Gröchenig
Faculty of Mathematics University of Vienna Oskar-Morgenstern-Platz 1 A-1090 Vienna, Austria
and
Michael Speckbacher
Institut de Mathématiques de Bordeaux
Université de Bordeaux
351, cours de la Libération - F 33405 TALENCE
France
Abstract.
We prove general kernel theorems for operators acting between coorbit spaces. These are Banach spaces associated to an integrable representation of a locally compact group and contain most of the usual function spaces (Besov spaces, modulation spaces, etc.). A kernel theorem describes the form of every bounded operator between a coorbit space of test functions and distributions by means of a kernel in a coorbit space associated to the tensor product representation. As special cases we recover Feichtinger’s kernel theorem for modulation spaces and the recent generalizations by Cordero and Nicola. We also obtain a kernel theorem for operators between the Besov spaces and .
Key words and phrases:
Kernel theorems, coorbit theory, continuous frames, operator representation, tensor products, Hilbert-Schmidt operators
2010 Mathematics Subject Classification:
42B35, 42C15, 46A32, 47B34
P.B. and M.S. were supported in part by the START-project FLAME (’Frames and Linear Operators for Acoustical Modeling and Parameter Estimation’; Y 551-N13) of the Austrian Science Fund (FWF), and K. G. was supported in part by the project P31887-N32 of the Austrian Science Fund (FWF)
1. Introduction
Kernel theorems assert that every “reasonable” operator can written as a “generalized” integral operator. For instance, the Schwartz kernel theorem states that a continuous linear operator possesses a unique distributional kernel , such that
[TABLE]
If is a locally integrable function, then
[TABLE]
and thus has indeed the form of an integral operator. Similar kernel theorems hold for continuous operators from [24, Theorem 5.2] and for Gelfand-Shilov spaces and their distribution spaces [21]. The importance of these kernel theorems stems from the fact that they offer a general formalism for the description of linear operators.
In the context of time-frequency analysis, Feichtinger’s kernel theorem [12] (see also [18] and [23, Theorem 14.4.1]) states that every bounded linear operator from the modulation space to the modulation space can be represented in the form (1) with a kernel in . The advantage of this kernel theorem is that both the space of test functions and the distribution space are Banach spaces and thus technically easier than the locally convex spaces and .
Recently, Cordero and Nicola [8] revisited Feichtinger’s kernel theorem and proved several new kernel theorems that “do not have a counterpart in distribution theory”. They argue that “this reveals the superiority, in some respects, of the modulation space formalism upon distribution theory”. While we agree full-heartedly with this claim, we would like to add a more abstract point of view and argue that the deeper reason for this superiority lies in the theory of coorbit spaces and in the convenience of Schur’s test for integral operators. Indeed, we will prove kernel theorems similar to Feichtinger’s kernel theorem for many coorbit spaces.
The main idea is to investigate operators in a transform domain, after taking a short-time Fourier transform, a wavelet transform, or an abstract wavelet transform, i.e., a continuous transform with respect to a unitary group representation. In this new representation every operator between a suitable space of test functions and distributions is an integral operator. The standard boundedness conditions of Schur’s test then yield strong kernel theorems.
The technical framework for this idea is coorbit theory which was introduced and studied in [15, 16, 17, 22] for the construction and analysis of function spaces by means of a generalized wavelet transform. The main idea is that functions in the standard function spaces, such as Besov spaces and modulation spaces, can be characterized by the decay or integrability properties of an associated transform (the wavelet transform or the short-time Fourier transform). In the abstract setting, is a locally compact group and is an irreducible, unitary, integrable representation of . Leaving technical details aside, the coorbit space consists of all distributions in a suitable distribution space, such that the representation coefficient is in the weighted space .
Next, let and be two locally compact groups, and and be irreducible, unitary, integrable representations of and respectively.
Let be a bounded linear operator between and . Our main insight is that such an operator can be described by a kernel in a coorbit space that is related to the tensor product representation of on the tensor product space . The following non-technical formulation offers a flavor of our main result in Theorem 3:
*A linear operator is bounded from to , if and only if there exists a kernel such that *
[TABLE]
for all .
This statement is not just a mere abstraction and generalization of the classical kernel theorem. With the choice of a specific group and representation one obtains explicit kernel theorems. For instance, using the Schrödinger representation of the Heisenberg group, one recovers Feichtinger’s original kernel theorem. The added value is our insight that the conditions on the kernel of [8] in terms of mixed modulation spaces [4] amount to coorbit spaces with respect to the tensor product representation. Choosing the -group and the continuous wavelet representation, one obtains a kernel theorem for all bounded operators operators between the Besov spaces and with a kernel in a space of dominating mixed smoothness. This class of function spaces has been studied extensively [32, 31] and is by no means artificial.
By using suitable versions of Schur’s test, it is then possible to derive characterizations for the boundedness of operators between other coorbit spaces. For example, in Theorem 7 we will prove the following, with :
[TABLE]
where the mixed-norm Lebesgue spaces and on are defined in (23) and (24) respectively.
The paper is organized as follows. In Section 2 we present the basics of tensor products and coorbit space theory. The theory of coorbit spaces of kernels with respect to products of integrable representations is developed in Section 3. Our main results, the kernel theorems, are proved in Section 4 and applied to particular examples of group representations in Section 5.
We note that our proofs require a meaningful formulation of coorbit theory. One can therefore prove kernel theorems also in the context of coorbit space theories [6, 9], e.g., for certain reducible representations.
2. Preliminaries on Tensor Products and Coorbit Spaces
2.1. Tensor Products and Hilbert-Schmidt Operators
The theory of tensor products is at the heart of kernel theorems for operators. Algebraically, a simple tensor of two vectors (in two possibly different Hilbert spaces) is a formal product of two vectors , and the tensor product is obtained by taking the completion of all linear combinations of simple tensors with respect to the inner product
[TABLE]
This tensor product is homogeneous in the following sense: . Note explicitly that the product is anti-linear in the second factor. In some books this is done by introducing the dual Hilbert space [25].
If each Hilbert space is an -space , then the simple tensor is just the product and the tensor product becomes the product space .
The connection between functions and operators arises in the analytic approach to tensor products. We interpret a function of two variables as an integral kernel for an operator. Thus a simple tensor of two functions becomes the rank one operator with integral kernel , and a general becomes a Hilbert-Schmidt operator from to . The systematic, analytic treatment of general tensor products of two Hilbert-spaces often defines the tensor product as a space of Hilbert-Schmidt operators between and . We note that his definition is already based on the characterization of Hilbert-Schmidt operators and thus represents a non-trivial kernel theorem [7]. Whereas the working mathematician habitually identifies an operator with its distributions kernel, we will make the conceptual distinction between tensor products and operators for our study of kernel theorems.
In the sequel we will denote the (distributional) kernel of an integral operator by and the abstract kernel in a tensor product by .
2.2. Coorbit Space Theory
Let be a locally compact group with left Haar measure , be a separable Hilbert space, and the group of unitary operators acting on . A continuous unitary group representation is called square integrable [11, 1], if it is irreducible and there exist such that
[TABLE]
A non-zero vector satisfying (3) is called admissible. For every square integrable representation there exist a densely defined operator such that , one has
[TABLE]
For fixed the representation coefficient is interpreted as a generalized wavelet transform. The orthogonality relation (4) then implies that is a multiple of an isometry from to . By using a weak interpretation of vector-valued integrals, (4) can also be recast as the inversion formula
[TABLE]
For the rest of this paper we assume without loss of generality that the chosen admissible vectors are normalized, i.e. .
The adjoint operator is formally defined by
[TABLE]
Other domains and convergence properties will be discussed later.
With this notation (5) says that for all admissible and normalized vectors , which in the language of recent frame theory means that is a continuous Parseval frame. By [5, Proposition 2.1] one can always assume that is -finite since we assume to be separable.
In coorbit theory one needs much stronger hypotheses on . The representation is called integrable with respect to a weight if there exists an admissible vector such that
[TABLE]
Let . We call a weight submultiplicative, if , and a function w-moderate, if it satisfies . If is -moderate, the weighted Lebesgue space is then invariant under left translation and under the right translation . Throughout this paper, we will assume that the weight satisfies
[TABLE]
where , , and denotes the modular function of .
Our standing assumption is that the representation of possesses an admissible vector such that . We denote the corresponding set by
[TABLE]
For fixed the linear version of
[TABLE]
is dense in . Let denote the anti-dual of , i.e., the space of anti-linear continuous functionals on . As is dense in , it follows that the inner product on extends to and so does the generalized wavelet transform.
The coorbit space with respect to is then defined by
[TABLE]
and is equipped with the natural norm
[TABLE]
With our assumptions on , the coorbit space is a Banach space [16]. Alternatively, for can be defined as the completion of with respect to this norm. Moreover,
[TABLE]
and
[TABLE]
for and -moderate weight . In the context of coorbit space theory the space serves as a space of test functions, and is the corresponding distribution space.
We quickly recall some of the fundamental properties of coorbit spaces, see for example [16, Theorem 4.1, Theorem 4.2 and Proposition 4.3].
Proposition 1**.**
Let , , and . Then the following properties hold:
- (i)
* is an isometry.* 2. (ii)
* is invariant with respect to and for all .* 3. (iii)
* is continuous.* 4. (iv)
. 5. (v)
Correspondence principle*: Let . There exists such that if and only if , where denotes convolution on .* 6. (vi)
Duality*: For , , we have , where the duality is given by*
[TABLE] 7. (vii)
The definition of is independent of the particular choice of the window function from . In particular, for arbitrary non-zero .
We furthermore need a result on the existence of atomic decompositions for the space , see [15, Theorem 4.7].
Theorem 2**.**
Let . There exists a discrete subset and a collection of linear functionals such that
[TABLE]
and the sum converges absolutely in .
3. Frames and Coorbit Spaces via Tensor Products
Let be two locally compact groups with unitary square integrable representations and . For the tensor representation ,
[TABLE]
acts on a simple tensor by
[TABLE]
It follows immediately that is a unitary representation of on . Moreover, is irreducible (e.g., by [34, Section 4.4, Theorem 6]). Note that the order of indices is in agreement with the formulation of the kernel theorem in Theorem 3.
If we interpret the simple tensor as the rank one operator with , then we can write (12) as
[TABLE]
where the contragredient representation of is defined as , see [34, Section 3.1].
In case we treat the tensor product as a space of Hilbert-Schmidt operators, acts on as
[TABLE]
The generalized wavelet transform of a simple tensor with respect to a “wavelet” is given by
[TABLE]
Thus, the wavelet transform of the tensor product representation factors into the product of wavelet transforms on and . Strictly speaking, we would have to write to indicate the underlying representation, but we omit the reference to the group to keep notation simple.
Throughout this paper we consider only separable weights with , and , where is submultiplicative and is -moderate. Moreover we write . It follows from (3) that the tensor representation of two square-integrable representations is again square-integrable and that the tensor of two admissible vectors and is admissible for . Likewise, if and , , then (where we assume that , , satisfies (7)). Therefore all definitions and results of Section 2.2 hold for the representation and . In particular, the orthogonality relation (4), the inversion formula (5), Proposition 1 and Theorem 2 hold for suitable admissible vectors .
4. Kernel Theorems
In this section we derive the general kernel theorems for operators between coorbit spaces. The basic idea comes from linear algebra, where a linear operator is identified with its matrix with respect to a basis. In coorbit theory the basic structure consists of the vectors . Thus in analogy to linear algebra we try to describe an operator by the kernel (= continuous matrix)
[TABLE]
This can be seen as a continuous Galerkin like representation of the operator [2, 3]. The idea goes back to coherent state theory [30, Chpt. 1.6]. One of its goals is to associate to every operator a function or symbol , and (14) is one of the many possibilities to do so.
Assume that , and , i.e., maps “test functions” to “distributions”. By using the inversion formula (5) for and applying to it, it follows that formally
[TABLE]
and furthermore
[TABLE]
Let
[TABLE]
be the integral operator with the kernel . Then (15) can be written as
[TABLE]
or equivalently,
[TABLE]
Using this factorization, the computation in (15) can be given a precise meaning on coorbit spaces. Identity (18) is the heart of the kernel theorems. The combination of the properties of the generalized wavelet transform (Proposition 1) and boundedness properties of integral operators yields powerful and very general kernel theorems.
We will first show the existence of a generalized kernel for operators mapping the space of test functions into the distribution space . Subsequently, we will characterize continuous operators in certain subclasses.
Theorem 3**.**
Let and be two locally compact groups, and be integrable, unitary, irreducible representations of , such that , for .
* Every kernel defines a unique linear operator by means of*
[TABLE]
for all and . The operator norm satisfies
[TABLE]
and
[TABLE]
* Kernel theorem: Conversely, if is bounded, then there exists a unique kernel , such that (19) holds.*
Proof.
Fix with , and let , be arbitrary. By (3) it follows that . Therefore, the duality in (19) is well-defined and
[TABLE]
Therefore, if we fix , the mapping is a bounded, anti-linear functional on , which we call . The map is clearly linear, and (19) defines a linear operator . The estimate (22) implies that
[TABLE]
and thus
[TABLE]
To prove the converse, we need to show that the mapping is one-to-one and onto.
Uniqueness: Let us assume that the kernel also satisfies
[TABLE]
for every , . By Theorem 2, there exists a discrete set such that every can be written as
[TABLE]
with unconditional convergence in and . Since \pi(\gamma_{i})\big{(}\psi_{2}\otimes\psi_{1}\big{)}=\pi(\gamma_{i,2})\psi_{2}\otimes\pi(\gamma_{i,1})\psi_{1}, we conclude that
[TABLE]
As this equality holds for every , it follows that .
Surjectivity: Let us assume that is bounded, then the kernel defined in (14) is an element of , because
[TABLE]
We claim that is a generalized wavelet transform. Precisely, there exists such that . To prove this claim, we use Proposition 1(v), which asserts that for some if and only if .
As , we may choose the most convenient order of integration and apply the reproducing formula of Proposition 1 (v) consecutively to the representations and . Using (3) we obtain
[TABLE]
At this point we note that by assumption on there exists a unique operator that satisfies
[TABLE]
for every and . By its definition, is weak∗-continuous. We continue with the integration over and obtain
[TABLE]
By Proposition 1 (v) there exists a kernel , such that . By the first part of the proof defines an operator by means of . In particular,
[TABLE]
Consequently, for all . This identity extends to all finite linear combinations of vectors and by Theorem 2 to . Thus and we have shown that the map from kernels to operators is onto.
The map is bounded and invertible. By the inverse mapping theorem we obtain that , which proves (20).
Remark 4**.**
It is crucial to interpret the brackets in (19) correctly. For utmost precision, we would have to write
[TABLE]
but we feel that this notation would distract from the analogy to distribution theory.**
The injectivity of the mapping from kernels to operators is closely related to an important property of the coorbit spaces . This so-called tensor product property has gained considerable importance in certain special cases [13, Theorem 7D] and [26], we therefore state and prove a general version. Recall that the projective tensor product of two Banach spaces and is defined to be
[TABLE]
The norm is given as over all representations of .
The following identification of the projective tensor product of and with the coorbit space is a generalization of Feichtinger’s original result for modulation spaces [13, Theorem 7D].
Theorem 5**.**
Under the general assumptions on the groups and the representations we have
[TABLE]
Proof.
Let . Then by Theorem 2 applied to , possesses the representation with and . Using Proposition 1 we obtain that
[TABLE]
Thus , and is continuously embedded into .
Conversely, let . Choose a representation with . Using Fubini’s theorem and Proposition 1 yields
[TABLE]
Thus, . The equivalence of the norms follows from the inverse mapping theorem. ∎
Once the kernel theorem provides a general description of operators between test functions and distributions, we may try to characterize certain classes of operators by properties of their kernel. Since on the level of the generalized wavelet transform such operators correspond to integral operators (see diagram), we may translate the various versions of Schur’s test to kernel theorems for operators between coorbit spaces. Following the procedure in [8, Theorem 3.3], we first formulate a general version of Schur’s test and then derive abstract kernel theorem.
We introduce two classes of mixed norm spaces. For two -finite measure spaces and , , and we define the spaces , and , by the norms
[TABLE]
and
[TABLE]
The following version of Schur’s test is folklore and can be found in [33, Proposition 5.2 and 5.4] or [27].
Proposition 6**.**
Let and be -finite measure spaces, , , and let be the integral operator with kernel .
* The operator is bounded from to , if and only if . In that case *
[TABLE]
* The operator is bounded from to , if and only if . In this case *
[TABLE]
We now characterize the boundedness of operators between certain coorbit spaces.
Theorem 7**.**
Let with , and be -moderate weights on . If is a bounded operator from to with kernel , then the following holds:
* is bounded from to , if and only if its kernel is in . Its operator norm satisfies *
[TABLE]
* is bounded from to , if and only if its kernel is in . Its operator norm satisfies*
[TABLE]
Proof.
Since and by (10), the kernel theorem is applicable to the operator , and there exists a kernel , such that .
Assume first that , which means that . By Proposition 6, the integral operator defined by the integral kernel is bounded from to . According to (18), factors as , where is an isometry from to , and is bounded from to by Proposition 1. Consequently is bounded from to . The boundedness estimate follows from
[TABLE]
Conversely, let be bounded from to . Then and the following estimates make sense:
[TABLE]
Since and is -moderate and thus satisfies , the last expression is bounded by
[TABLE]
Thus .
Part follows by using Proposition 6 instead of and is proved similarly.
The following diagram shows the connection between the different operators and spaces.
V_{\psi_{1}}$$k_{A}\ \in\ \mathcal{L}^{p,\infty}_{m_{1}^{-1}\otimes m_{2}}(G)$$A bounded boundedV_{\psi_{2}}$$V_{\Psi}$$L^{1}_{m_{1}}(G_{1})$${\mathcal{C}o_{\pi_{1}}L^{1}_{m_{1}}(G_{1})}\,$${\mathcal{C}o_{\pi_{2}}L^{p}_{m_{2}}(G_{2})}\,$$L^{p}_{m_{2}}(G_{2})$$K\ \in\ {\mathcal{C}o_{\pi}}\,\mathcal{L}^{p,\infty}_{m_{1}^{-1}\otimes m_{2}}(G)
Using interpolation between -spaces, Schur’s test can also be formulated as saying that an integral operator is bounded on all simultaneously, if and only if its kernel belongs to . The corresponding version for coorbit spaces is a consequence of Theorem 7 and an interpolation argument.
Corollary 8**.**
The following conditions are equivalent:
- (i)
* is bounded for every .* 2. (ii)
Both and are bounded. 3. (iii)
.
Clearly one can now translate every boundedness result for an integral operator into a kernel theorem for coorbit spaces. As a simple, but important example we offer a sufficient condition for regularizing operators, i.e., of operators that map distributions to test functions.
Theorem 9**.**
Under the assumptions of Theorem 3, if the unique kernel of the operator satisfies , then is bounded from to .
Proof.
Consider the integral operator as in the proof of Theorem 7 and observe is a sufficient condition for to be bounded by Schur’s test. ∎
4.1. Discretization
Coorbit theory guarantees the discretization of the coorbit spaces via atomic decompositions and Banach frames. For our purposes, it is sufficient to state a shortened and simplified version of [22, Theorem 5.3]. Let be one of the function spaces or , and the natural sequence space associated to .
Proposition 10**.**
If satisfies
[TABLE]
for a compact neighborhood of , then there exists a discrete subset , and constants , such that
[TABLE]
Corollary 11**.**
*Let a discrete set such that satisfies (28) for and . If is a bounded operator from to with kernel , then the following holds:
is bounded if and only if*
[TABLE]
* Likewise is bounded if and only if*
[TABLE]
Proof.
By Theorem 7 has a kernel in , and . By (28), the expression in (29) is an equivalent norm for . The proof of works exactly the same.
5. Examples
5.1. Modulation spaces
The Weyl-Heisenberg group is defined by the group law
[TABLE]
Let denote the translation, and the modulation operator. The operator for defines a unitary square-integrable representation of acting on , for which every nonzero vector in is admissible. Since the phase factor is irrelevant for the definition of coorbit spaces, it is convenient to drop the trivial third component, and consider the time-frequency shift . Formally, we treat the projective representation of instead of the unitary representation of . The transform corresponding to is nothing else but the short-time Fourier transform
[TABLE]
The coorbit spaces associated to coincide therefore with the coorbit spaces associated to . These are the modulation spaces which were first introduced by Feichtinger in [14] as certain decomposition spaces and subsequently were identified with the coorbit spaces of the Heisenberg group [18]. We refer to the standard textbooks [20, 23] for more information on time-frequency analysis.
Theorem 3 asserts that every bounded operator from to possesses a kernel , such that for . Let us elaborate in detail what the kernel theorem asserts in this case: for , the tensor representation acts on the simple tensor as
[TABLE]
Thus except for the phase factor the tensor representation is just the time-frequency shift acting on . Consequently, the coorbit spaces with respect to the product group are again modulation spaces, this time on . For the coorbit of we compare the norms
[TABLE]
and
[TABLE]
which are obviously equal. In this case Theorem 3 is therefore just Feichtinger’s kernel theorem: For there exists a unique kernel , such that .
The recent extension of Feichtinger’s kernel theorem by Cordero and Nicola [8] can be seen in the same light. Let us explain the difference in the formulations. Our approach considers the generalized wavelet transform
[TABLE]
of the kernel. The conditions of Theorem 7 are formulated by mixed norms acting simultaneously on the variables and on . The treatment in [8] uses the short-time Fourier transform on
[TABLE]
which is the same transform, except for the order of the variables. In [8] it was therefore necessary to reshuffle the order of integration of time-frequency shifts and to use the notion of mixed modulation spaces, which were studied in [4, 29]. The new insight of our formulation is that the mixed modulation spaces are simply the coorbit spaces with respect to the tensor product representation.
The special case of Theorem 7 for the Weyl-Heisenberg group and the weights for states the following: Fix and let be an operator from to . Then for , and we have
[TABLE]
Regularizing operators from to were studied recently studied by Feichtinger and Jakobsen [19]: they characterized a subclass of this space of operators by an integral kernel in . The sufficiency of this result in a coorbit version is contained in Theorem 9.
5.2. Wavelet Coorbit Spaces and Besov Spaces
The affine group is given by the group law where and . Its left Haar measure is given by . Let denote the dilation operator. Then defines an unitary, square-integrable representation of on .
Let now . The continuous wavelet transform is defined as
[TABLE]
and the admissibility condition (3) reads as
[TABLE]
It is well-known that the coorbit spaces associated to the representation are the homogeneous Besov spaces. See the textbooks [10, 28] for details and further expositions of wavelet theory. For brevity, we consider only the coorbit spaces with respect to the weighted -spaces with the weight function for . Note that . Then by [15, Section 7.2]. In particular and . In this example Theorem 3 states that an operator is bounded if and only if its associated kernel is in . At first glance not much seems to have been gained by this formulation, but it turns out that the coorbit spaces of the tensor product of are well understood in the theory of function spaces under the name of *Besov spaces of dominating mixed smoothness. * In particular, can be identified with the Besov space of dominating mixed smoothness . See [32], Def. A.4 and [31]. Moreover, Theorem 7 yields a characterization of continuous operators between certain Besov spaces:
[TABLE]
The case for was already formulated in a discrete version by Meyer [28, Section 6.9, Proposition 6].
Theorem 12**.**
Let be a wavelet basis with , and assume that has compact support and satisfies sufficiently many moment conditions so that the assumption of Proposition 10 is satisfied. An operator is bounded if and only if
[TABLE]
Proof.
Set , , recall that and apply Corollary 11.
5.3. The Case of Two Distinct Representations
For most applications it suffices to consider a single group and its product group . Our formulation with two different group allows us to study operators acting between coorbit spaces associated with different group representations. Using the representations of the Weyl-Heisenberg group and the affine group of Sections 5.1 and 5.2, one can characterize the boundedness of operators between certain modulation spaces and Besov spaces by properties of their associated kernels. Theorem 7 now reads as follows:
[TABLE]
As a special case one obtains a characterization of the bounded operators from to . Since , they are completely characterized by the membership of their kernel in .
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