Abstract
We analyze the notion of reproducing pairs of weakly measurable functions, a generalization of continuous frames. The aim is to represent elements of an abstract space Y as superpositions of weakly measurable functions belonging to a space , where is a measure space. Three cases are envisaged, with increasing generality: (i) Y and Z are both Hilbert spaces; (ii) Y is a Hilbert space, but Z is a pip-space; (iii) Y and Z are both pip-spaces. It is shown, in particular, that the requirement that a pair of measurable functions be reproducing strongly constrains the structure of the initial space Y. Examples are presented for each case.
Keywords:
reproducing pairs; continuous frames; upper and lower semi-frames; partial inner product spaces MSC:
41A99; 46Bxx; 46C50; 46Exx
1. Introduction
Representing functions in terms of simple ones, with a small number of them, if possible, is a standard problem in analysis, in particular in signal and image processing, where transmission imposes severe constraints. Signals are usually taken as square integrable functions on some manifold, hence they constitute a Hilbert space.
More precisely, given a separable Hilbert space , one wishes to represent an arbitrary element by a superposition of simpler, basic elements , with a countable index set:
One usually requires that the sum converges adequately (e.g., in norm and unconditionally) and that the coefficients are unique (if possible) and easy to compute. There are many possibilities for obtaining that result, the simplest ones being that be an orthonormal basis or a Riesz basis.
These two notions indeed solve the problem, but they are very rigid and lead usually to slowly converging infinite expansions. Thus frames were introduced for ensuring a better flexibility, originally in 1952 by Duffin and Schaeffer [1] in the context of nonharmonic analysis. The notion was revived by Daubechies, Grossmann and Meyer [2] in the context of wavelet theory and then became a very popular topic, in particular in Gabor and wavelet analysis [3,4,5,6]. The reason is that a good frame in a Hilbert space (that is, a frame where the ratio of the frame bounds is close to 1) is almost as good as an orthonormal basis for expanding arbitrary elements (albeit non-uniquely) and is often easier to construct and has in many cases additional structural properties. Let us first recall that a sequence is a discrete frame for a Hilbert space if there exist constants (the frame bounds) such that
The frame bounds are usually denoted by A and B in the literature, but this conflicts with the notation for operators. Here we follow our monograph [7].
As a matter of fact, most frames considered in applications are discrete, for instance in signal or image processing [4]. Yet continuous frames offer interesting mathematical problems. They have been introduced originally by Ali, Gazeau and one of us [8,9] and also, independently, by Kaiser [10]. Since then, many papers dealt with various aspects of the concept, see for instance [11,12,13,14].
However, there are situations where it is impossible to satisfy both frame bounds at the same time. Indeed, the two bounds are independent: A sequence that verifies the upper bound may not have a lower bound and a sequence that verifies the lower bound may be unbounded. To give a (simple) example, take an orthonormal basis . Then the sequence satisfies the upper bound, but has no lower bound, whereas the sequence satisfies the lower bound, but not the upper one. Therefore, several generalizations of frames have been introduced. Semi-frames [15,16], for example, are obtained when functions only satisfy one of the two frame bounds. Thus one speaks of upper or lower semi-frames. It turns out that a large portion of frame theory can be extended to this larger framework.
More recently, a new generalization of frames was introduced by Balazs and Speckbacher [17], called reproducing pairs. Here, given a measure space , one considers a pair of weakly measurable functions , instead of a single mapping, and one studies the correlation between the two (a precise definition is given below). This definition also includes the original definition of a continuous frame [8,9] to which it reduces when . The choice of the mappings and gives more freedom, but it leads to the problem of characterizing the range of the analysis operators, which in general may not be contained in , as in the frame case. Therefore, it is natural to extend the theory to the case where the weakly measurable functions take their values in a partial inner product space (pip-space) [7]. Actually we will go further and consider a more general construction. Namely we want to represent elements of an abstract space by weakly measurable functions , belonging to a space , in such a way that the (formal) inner product
is well defined. The interesting point is that the construction extends naturally from the simple case of a frame to the more general case just outlined, and this is the rationale behind the present paper. Nevertheless, since the techniques needed in this general case are very similar to those used in the previous ones, we have sketched them in these simpler cases first, in order to make the paper self-contained. Further information may be found in the original papers or in the review paper [18] that we follow closely.
The paper is organized as follows. In Section 2, we review the notions of frames, semi-frames and reproducing pairs and we recall their salient properties. In Section 3, we consider the case where Y and Z are both Hilbert spaces, which corresponds to genuine frames. In particular we construct and analyze the so-called coefficient spaces , which are Hilbert spaces in conjugate duality when is a reproducing pair. In Section 4, motivated by the relation (3), we take for target space a pip-space , in particular a lattice of Hilbert or Banach spaces (LHS/LBS). In Section 5, we go one step further and take for the initial space another pip-space . In particular, we see how the requirement of having a reproducing pair affects the structure of the initial space Y. Finally, we conclude by an Appendix A, in which we recall the main definitions and notations about pip-spaces (LHS/LBS) and operators on them.
2. Preliminaries
Before proceeding, we list our definitions and conventions. We work in a (separable) Hilbert space , with the inner product linear in the first factor. If A is an operator on , we denote its domain by , its range by and its kernel by . The set of all invertible bounded operators on with bounded inverse is denoted . We will consider throughout weakly measurable functions , i.e., is -measurable for every . Here is a locally compact, -compact space with a Radon measure .
The weakly measurable function is called continuous frame if there exist constants and (the frame bounds) such that
Remark 1.
The geometry of the Hilbert space imposes a number of constraints that severely limit the existence of continuous families acting as bases or frames. Apart from the case of a separable Hilbert space where orthonormal or Riesz bases cannot be uncountable, there are more general situations where, for instance, Riesz bases cannot be continuous, but they are necessarily discrete, in a certain sense [19,20,21,22]. Nevertheless, this result is essentially of theoretical nature and does not affect the interest for continuous frames in applications. On the other hand, continuous frames do really exist in more general frameworks (rigged Hilbert space, pip-space) as shown in [23,24,25] and in the present paper. This fact constitutes a further motivation for going beyond Hilbert spaces.
Given the continuous frame , we define the analysis operator as
and the corresponding synthesis operator as
the integral being understood in the weak sense. Clearly both operators are bounded. We set , i.e.,
Thus the so-called frame or resolution operator is self-adjoint, invertible, bounded with bounded inverse , that is, .
In particular, if X is a discrete set with being a counting measure, we recover the standard definition (2) of a (discrete) frame [1,3,4].
The weakly measurable function is said to be μ-total if , -a.e., implies , that is, . Following [15,16], we will say that a family is an upper (resp. lower) semi-frame, if it is -total in and satisfies the upper (resp. lower) frame inequality. For the sake of completeness, we recall the definitions. A weakly measurable function is an upper semi-frame if there exists such that
Note that an upper semi-frame is also called a (total) Bessel mapping in the literature [13].
On the other hand, a measurable function is called a lower semi-frame if it satisfies the lower frame condition, that is, there exists a constant such that
Clearly, (9) implies that the function is -total in .
If is a measurable function, the operator , formally defined as for frames, takes values in the space of measurable functions on and the adjoint is, in general, meaningless. has a natural domain in Hilbert space, namely,
but this domain, in general, is not dense and nothing guarantees that it does not reduce to .
If the measurable function is an upper semi-frame, the definition implies that is contained in . If a measurable function is a lower semi-frame, is injective and has closed range.
In the lower case, the definition of the frame operator must be changed, since need not be densely defined, so that may not exist. Instead, following [15] (Section 2) one defines the synthesis operator as
on the domain of all elements for which the integral in (10) converges weakly in , and then . With this definition, it is shown in [15] (Section 2) that is unbounded and is bounded.
All these objects are studied in detail in our previous papers [15,16]. In particular, it is shown there that a natural notion of duality exists, namely, two weakly measurable functions are dual to each other (the relation is symmetric) if one has
A new generalization of frames was introduced recently by Balazs and Speckbacher [17], namely, reproducing pairs. Given a measure space , one considers a couple of weakly measurable functions , instead of a single mapping. The advantage is that no further conditions are imposed on these functions, which results in an increased flexibility.
More precisely, the couple of weakly measurable functions is called a reproducing pair [17,26] if (i) the sesquilinear form
is well-defined and bounded on , that is, , for some and every ; and (ii) the corresponding bounded (resolution) operator belongs to .
Under these hypotheses, one has
the integral on the r.h.s. being defined in weak sense. If , we recover the notion of continuous frame, as introduced in [8,9], so that we have indeed a genuine generalization of the latter.
Notice that, if , the frame operator is in general neither positive, nor self-adjoint, since . However, if is a reproducing pair, then is also a reproducing pair, for which the corresponding frame operator is the identity, that is, and are in duality. Thus, there is no restriction of generality to assume that [17]. The only thing that can happen is to replace some norms by equivalent ones.
3. The Case and , Both Hilbert Spaces
As mentioned in Section 1, we begin with the case where the initial space and the target space are both Hilbert spaces, which is characteristic of a reproducing pair as originally defined [17].
Given a weakly measurable function , let us denote by the space of all measurable functions such that the integral exists for every and defines a bounded conjugate linear functional on , i.e., such that
Clearly, if is a reproducing pair, all functions belong to .
By the Riesz lemma, we can define a linear map , which we call the synthesis operator, by the weak relation
Next, we define the vector space
and equip it with the norm
where we have put for . Clearly, is a normed space, called the coefficient space of . However, the norm derives from an inner product. First, the map , is an isometry of into . Next, one defines on an inner product by setting
Finally, the norm defined by coincides with the norm defined in (16), since one has indeed
Thus is a pre-Hilbert space with inner product .
We denote by the Hilbert dual space of , that is, the set of continuous linear functionals on . The structure of this dual will be elucidated below. The (dual) norm of is defined, as usual, by
Now we define a conjugate linear map by
Notice that this map is conjugate linear, so it should not be confused with the linear map introduced in (5).
Of course, (18) means that , for every . Thus , the adjoint map of . By (13) it follows that is continuous. This implies that
where the first summand denotes the closure of . Hence , if is complete.
By modifying in an obvious way the definition given in Section 2, we say that is μ-total if .
A first preliminary result reads as follows.
Proposition 1.
If is a reproducing pair, then .
For the proof, notice that, since , for every , there exists a unique such that . By (12), we can conclude that
that is, . Notice that, if is a reproducing pair, both functions are necessarily -total, which already implies that is dense in , by (19).
For future use, we note that, if is a reproducing pair, then we have the relation [26] (Theorem 3.12).
The crucial step for characterizing the elements of is the following result.
Theorem 1.
If is a reproducing pair, then every bounded linear functional F on , i.e., , can be represented as
with . The residue class is uniquely determined.
Proof.
We proceed in several steps. First, if F is a continuous linear functional on , then there exists a unique , such that
Indeed, given , there exists such that
Let be the continuous functional on defined by
The functional is well-defined. Indeed, if , then . Hence, and . Thus there exists a unique such that
and . In conclusion, (22) holds true and , where is the dual norm defined in (17).
Conversely, every obviously defines a continuous linear functional F by (22) since for every .
Finally, since , we have the representation (21). Uniqueness is immediate. □
Remark 2.
Several of the previous statements hold true without the assumption that is a reproducing pair, see [26] (Section 3) for details.
The lesson of Theorem 1 is that the map
is well-defined and conjugate linear. On the other hand, implies easily . Therefore can be identified with a closed subspace of , where the overbar denotes the complex conjugate.
Actually, there is more: if is a reproducing pair, and can be identified. The proof relies on two technical lemmas which can be found in [26] (Lemmas 3.10 and 3.11). These imply that the map defined in (23) is surjective. Hence, , where ≃ denotes a bounded isomorphism and the norm is the dual norm of . Finally, for every , there exists such that . In conclusion, one obtains the main result of [26], namely:
Theorem 2.
If is a reproducing pair, the spaces and are both Hilbert spaces, conjugate dual of each other with respect to the sesquilinear form
which coincides with the inner product of whenever the latter makes sense.
This is true, in particular, for , since then is a continuous frame and is a closed subspace of .
In addition, the converse of Theorem 2 holds if and are both -total: in that case, is a reproducing pair if and only if and are Hilbert spaces, conjugate dual of each other with respect to the sesquilinear form (24).
In fact, there is more. In a recent paper [22], it is shown that (and thus also , by symmetry), is a reproducing kernel Hilbert space (RKHS) [27]. In order to see this, take an orthonormal basis in . Then the family , defined by forms an orthonormal family in , since one has . Thus forms an orthonormal basis in
By [22] (Theorem 23), it follows that is a reproducing kernel Hilbert space and one has (compare (20))
Finally, the reproducing kernel of is given by
Actually, the kernel is also reproducing, but for the inner product of , whereas (25) is reproducing for the inner product and is therefore the correct reproducing kernel of .
4. The Case , a Hilbert Space, and , a PIP-Space
Clearly, the inner product (24) need not always be defined, it is a partial inner product on the space of measurable functions on . This obviously suggests to take for the target space a pip-space around , as we have proposed in [23], that we mostly follow in this section. As for the relevant notions about pip-spaces, we have collected them in the Appendix A.
4.1. The Case Where Z Is a Rigged Hilbert Space
The simplest example of a pip-space is a rigged Hilbert space (RHS). Let indeed be a RHS with reflexive (hence t and coincide with the respective Mackey topologies). Given the measure space , we denote by the sesquilinear form expressing the duality between and . This form replaces the inner product used so far. As usual, we suppose that this sesquilinear form extends the inner product of (and ). This allows to build the triplet above.
Let be weakly measurable functions from X into . Instead of (11), we consider the sesquilinear form
and we assume that it is jointly continuous on . Writing
we see that the operator belongs to , the space of all continuous linear maps from into .
At this point, we have a choice. A first possibility is to require that the sesquilinear form be well-defined and bounded on in the topology of . Then extends to a bounded sesquilinear form on and the discussion of Section 3 may be essentially repeated verbatim. Thus this choice gives almost nothing new.
Another possibility is to assume that the form is jointly continuous on , with no other regularity requirement. In that case, the vector space must be defined differently, taking into account the (locally convex) topology of and . Instead of (13), we require that the integral exists for every and defines a continuous conjugate linear functional on . As before, we define (weakly) a linear map by the following relation
Next, we define again the vector space In order to introduce a topology on , we consider a bounded subset of and we define the seminorm
This means, we are defining the topology of by means of the strong dual topology of which we recall is defined by the seminorms
where runs over the family of bounded subsets of . Thus is a locally convex space. As said above, the reflexivity of entails that is equal to the Mackey topology .
Next we consider the dual of the space , that is, the set of continuous linear functionals on . As topology on , we take the strong dual topology. This being done, almost all the results of Section 3 may be deduced. In particular, Theorem 1 remains true, under the form.
Theorem 3.
Under the condition (26), every continuous linear functional F on , i.e., , can be represented as
with . The residue class is uniquely determined.
As in the previous case, one may prove again that can be identified with a closed subspace of , but we cannot go further. Indeed the previous results rely heavily on Hilbert space methods, which are not available here.
4.2. The Case Where Z Is a LHS/LBS
The next choice is to take for Z a genuine pip-space, while keeping for the initial space Y a Hilbert space . For simplicity, we restrict ourselves to a lattice of Banach spaces (LBS) or a lattice of Hilbert spaces (LHS) [7], which is amply sufficient for applications. For instance, , the lattice generated by or a lattice of weighted spaces.
Let be a LBS or a LHS of -measurable functions with the property
Thus the central Hilbert space is and the spaces are dual of each other with respect to the inner product. The partial inner product, which extends the inner product of , is denoted again by . As usual we put and According to the general theory of pip-spaces [7], the vector space V is the algebraic inductive limit of the ’s (see the Appendix A.1). Thus means that for some .
Let be weakly measurable functions from X into . In the case of Section 3, if is a reproducing pair, the frame operator may be written as
which is well defined for all . But now the inner product is only partial, and this motivates the next assumption. In view of (31), (32), and the definition of V, we assume that the following condition holds:
- ()
- such that and .
We recall that is the conjugate dual of . In this case, then
defines a sesquilinear form on and one has
If is bounded as a form on (this is not automatic), there exists a bounded operator in such that
Then is a reproducing pair if .
In the sequel, we will often need the map to be continuous. In general, however, we have to assume it explicitly, unless the space satisfies additional conditions.
If is continuous, then exists and it is continuous too. By definition, if ,
Thus,
Of course, what we have said about holds in the very same way for . Assume now that for some and continuously. Then, so that is a well-defined bounded operator in , given by
the last equality following also from (34). Of course, this does not yet imply that , thus we do not know whether is a reproducing pair.
Let us now return to the pre-Hilbert space . First, the defining relation (13) must be written as
Since , the integral is well defined for all . This means, the inner product on the l.h.s. is again the partial inner product of V. . Hence, we may rewrite (36) as
Next, by (31), one has, for ,
where the last inequality follows from the assumption of continuity of . Hence indeed , so that .
As for the adjoint operator, we have . Then we may write, for , , thus is the restriction from to of the operator given in (14), which reads now as
Thus .
Next, the construction proceeds as in Section 3. The space , with the norm , is a pre-Hilbert space. Then Theorem 2 remains true, namely,
Theorem 4.
If is a reproducing pair, the spaces and are both Hilbert spaces, conjugate dual of each other with respect to the sesquilinear form (24), namely,
which coincides with the inner product of whenever the latter makes sense.
More precisely, we may state
Proposition 2.
Let be a reproducing pair. Then, if and continuously, one has
In these relations, the equality sign means an isomorphism of vector spaces, whereas ≃ denotes an isomorphism of Hilbert spaces.
Since and are both Hilbert spaces, the relations (38) suggest to take for Hilbert spaces as well, that is, take for V a LHS. The simplest case is then a Hilbert chain, for instance, the scale (A2) built on the powers of a self-adjoint operator .
Choose a reproducing pair . Without loss of generality, we suppose that are dual to each other, that is, . We assume that is an upper semi-frame and is a lower semi-frame, dual to each other. It follows that . By Condition (), there is an index such that and continuously, so that we may identify and . Then, according to Proposition 2, we have and , as vector spaces. Concrete examples will be given in Section 6.
5. The Case Where and Are Both PIP-Spaces
In the previous sections, we have taken for the initial space Y a single abstract Hilbert space . Now we will go one step further and take instead an abstract LBS or a LHS , with , while keeping for Z the space , a LBS or a LHS of complex measurable functions over the usual measure space , with .
Let be two weakly measurable functions on X, with values in Y. In the present context, weak measurability means that, for any such that and , the complex functions and are -measurable for every .
Define two analysis operators as follows:
where the inner product is the partial inner product of Y.
Definition 1.
Given such that and , assume there exists such that
with and continuous, so that and are continuous also. In that case, we say that is an admissible couple for .
Given an admissible couple for , the sesquilinear form
is well-defined on and we have
Then there exists a continuous operator such that
More precisely, in the pip-space operator language (see the Appendix A), has a (necessarily continuous) representative . It is easily checked that . The operator is called the frame operator associated to the pair .
The map has an adjoint defined by
An easy computation shows that
Hence, .
5.1. Construction of Coefficient Spaces
Fix an admissible couple for . Denote by the space of all measurable functions such that the integral
exists for every and defines a continuous conjugate linear functional on That is, there exists such that
As in the previous cases, we refer to as the coefficient space of . The space is defined in a similar way.
Since the sesquilinear form is bounded, by (40), it is clear that all functions belong to since, by assumption,
exists and is bounded.
Then, following the familiar pattern, we can define a linear map , which we call again the synthesis operator by the following relation
Set and . By definition, is called -independent whenever ; in that case, of course, .
The space can be made into a normed space by defining
which implies that the operator defined by is continuous, injective and an isometry.
Proposition 3.
The space is a Banach space if, and only if, is a closed subspace of .
Proof.
Suppose that is closed and let be a Cauchy sequence in . Then, by definition is a Cauchy sequence in ; hence it converges to . Since is closed, for some It is clear that if is another function such that , then and then . Moreover
This proves that is complete. Conversely, suppose that is a Banach space and let , . Then
Hence there exists such that . This in turn implies that and, therefore . We conclude that is closed. ☐
Thus, if is complete, it has a closed image and its inverse is also continuous (but not necessarily everywhere defined).
Note that, if Y is a LHS, the norm is Hilbertian, so that is a pre-Hilbert space (same argument as in Section 3).
The same result applies to , which is also a pre-Hilbert space in the LHS case, i.e., is an isometry.
It is shown in [23] (Theorem 3.4), that a linear functional F on is continuous if, and only if, there exists such that
Then, taking into account the relations (39) and (40) and the fact that , we see that every can be represented as
with . Hence, the dual space of , with respect to the sesquilinear form given by the inner product, can be identified with a space of measurable functions containing all functions .
5.2. Compatible Pairs
Fix an admissible couple for . As seen above, the sesquilinear form
is well defined and bounded on . With a proof similar to that of [23] (Theorem 3.6) or that of Section 4, one shows that the dual can be identified with a closed subspace of , the space of conjugates of elements of . On the other hand, it was proved in [26] that, for a reproducing pair of -valued weakly measurable functions , the spaces and are both Hilbert spaces in conjugate duality to each other (see Theorem 2).
In the same vein as in Section 3, in particular Theorem 2, we define a new concept, generalizing to the present situation what has been done in [25].
Definition 2.
Let be an admissible couple for . We say that are compatible if is topologically isomorphic to and , the conjugate dual of , is topologically isomorphic to . Thus we identify the dual with and the conjugate dual with .
This definition implies that the spaces and are reflexive spaces enjoying the duality properties mentioned above, which we write shortly as and . Then we have
This proves that is a compatible pair if and only if is a compatible pair.
In what follows, for simplicity, we will consider pairs () with both -independent. In this case , . Hence we will use the notation , for these spaces.
As a matter of fact, compatible pairs and reproducing pairs are closely related, as shown in the following result.
Theorem 5.
Let be an admissible couple for , with both μ-independent and μ-total. Consider the following statements:
- (i)
- () is a compatible pair;
- (ii)
- The operator is bounded with bounded inverse, that is, () is a reproducing pair.
Then, if is complete, (i) implies (ii). On the other hand, (ii) always implies (i). Thus, if is complete, the two statements are equivalent.
Proof.
Since are -independent, .
(i) ⇒ (ii): If is an admissible couple for the operator is continuous from into . It is injective, since is -independent and is -total. Next we show that it is also surjective. We first prove that is dense in . Suppose that is such that for every . Thus,
In particular this is true if we take , with . The -independence of implies that for almost every . Hence , because is -total.
By Proposition 3, is closed in . Hence, . Therefore, for every there exists a unique such that . This implies that:
By the definition of compatible pairs, the conjugate linear functional on defined by:
is continuous. Then, as discussed at the end of Section 5.1, there exists a unique such that
Hence, in particular
In conclusion,
This implies that . Hence is bounded, by the inverse mapping theorem.
(ii) ⇒ (i): Let , the dual of ; then, as discussed at the end of Section 5.1 there exists such that:
We show that g is unique. Suppose that there exists another satisfying the same condition. Then it follows that:
In particular, this is true for , for every . Thus:
Hence, , for every . However, since , we conclude that , for every and this, in turn, implies that . Therefore, we can define a map , where g is the unique element of such that . This map is an isomorphism of vector spaces. Indeed, it is clearly injective. On the other hand, if , the functional
is in and satisfies . It is clear that the function is an element of . Assume that there exists another function such that
This implies that:
Take , , then . Hence . Then we can define a linear map:
where denote the dual space of . The map is clearly injective. As we have seen , for every , where . Indeed, . Hence , thus . Now we put . Hence is a conjugate linear map of into . We want to prove that coincides with .
First we have
This inequality implies that is closed in .
Next, we prove that is also dense in . If it was not so, there would be a nonzero continuous linear functional F on such that for every . Hence, there would exist such that:
and therefore
This implies that for all . However, since , this yields a contradiction. Let us now consider the map defined in (45). An immediate consequence of the equality is that is surjective. This implies that the conjugate dual of can be identified with , the space of conjugates of elements of . □
5.3. The General Case
Take again an admissible couple for , assuming both to be -independent and -total, for simplicity. We know from Section 5.2 that the dual can be identified with a closed subspace of , the space of conjugates of elements of . In addition, is complete as a dual.
Assume first that is a compatible pair. Then we have and . Notice that both spaces and are Banach spaces in general, but they are Hilbert spaces in the case of a LHS since then the norm (43) is Hilbertian [26]. Now and are continuous and bijective, hence the inverse maps and are also continuous by the inverse mapping theorem. Thus and are isomorphisms. In addition, they are isometries, by (43). Thus et are isometric and so are the respective duals and and the same for . Since (as spaces of measurable functions), we can say that and have equal norms, hence we have . Thus this is a necessary condition for to be a compatible pair for the admissible couple .
If the condition is satisfied, it follows that the frame operator maps onto itself continuously and has a bounded inverse, since the representative is invertible, which means that is an invertible pip-space operator [28] (see Appendix A.2).
More generally, given an admissible couple for , we may ask under which conditions the latter is a compatible pair, which is the same thing as a reproducing pair, according to Theorem 5. First, we need , that is, there must exist such that and continuously. In that case, since exists, so are the representatives , where The required condition is then that one of these representatives be invertible. This replaces the condition used for reproducing pairs [23,26].
5.4. Comparison with the Case
As we said in Section 3, the case treated in [23] (Section 4) amounts to take for the initial space Y a single Hilbert space . We will adapt here the results of that paper to the new situation, described in Definition 1.
Let us suppose that the spaces have the following property:
- ()
- If in , then, for every compact subset , there exists a subsequence of which converges to almost everywhere in K.
The property () is satisfied by -spaces [29] (Theorem 3.12), but presumably not in general. It is satisfied, however, if one has a continuous embedding of a given Banach space of measurable functions into , which applies, for example, to all the Banach function spaces in the sense of Luxemburg-Zaanen [30]. Notice that Condition () concerns only the target space Z, it is independent of the initial space Y.
Let be an admissible couple for . Instead of , we have that , and . Let be an arbitrary element of (an assaying subspace [7], which is a Banach space or a Hilbert space). Following [23] (Section 4), we define
In particular, means . According to Definition 1, this condition is satisfied for , but not necessarily otherwise.
Then we have the following results, corresponding to Proposition 4.2 and Corollaries 4.3 and 4.4 of [23].
Proposition 4.
Assume that () holds for . Then:
- (i)
- is a closed linear map.
- (ii)
- If for some , , then is continuous.
- (iii)
- If and , the form Ω is bounded on , that is, .
Proof.
The proof of (i) follows verbatim that of [23] (Proposition 4.2), simply replacing by . The same is true for (ii) and (iii) with the two corollaries. □
By definition, is continuous. If and condition () holds, implies that is continuous. If and we do not know whether the condition holds, we will have to assume explicitly that is continuous.
Suppose now that for some , the maps and are continuous (automatic for ). Then, , so that is a well-defined bounded operator from to . Of course, this does not yet imply that , or any other representative, has a bounded inverse. Hence we do not know whether is a reproducing pair, even if we impose the necessary condition .
6. Examples
In this section, we present concrete examples that illustrate all three types of reproducing pairs described in the previous sections.
6.1. A Purely Hilbertian Reproducing Pair
Several discrete examples may be found in [26] (Section 6.1). Here, however, we restrict ourselves to continuous examples, which are more interesting.
If , consider the continuous wavelet system . Let and suppose they satisfy the following cross-admissibility condition:
As shown in [6] (Theorem 10.1), this condition implies the well-known orthogonality relations of the corresponding wavelet transform. Thus, is a reproducing pair for with For , the cross-admissibility condition (46) reduces to the classical admissibility condition
Considering the obvious inequalities
we see that condition (46) is automatically satisfied whenever and are both admissible, so that indeed is a reproducing pair.
However, nonadmissible wavelets may also generate reproducing pairs, as shown by the following trivial example. Take the Gaussian window , then which implies that is not a continuous wavelet frame. However, if one defines in the Fourier domain via , it follows that . Thus is a reproducing pair. This example clearly shows the increasing flexibility obtained when replacing continuous frames by reproducing pairs.
6.2. A Reproducing Pair with a PIP-Space Target
As discussed after Proposition 2, we take for V a LHS, more precisely the scale (A2) built on the powers of the self-adjoint operator . Thus, according to the discussion at the end of Section 4.2, there is an index such that and continuously, where we have
Actually one may give an explicit example, using a Sobolev-type scale [23] (Section 5). Let be a reproducing kernel Hilbert space (RKHS) of (nice) functions on the measure space , with kernel function , that is, (we could also take another measure space ) [27]. The corresponding reproducing kernel is . Choose a weight function , the analog of the weight considered in the Sobolev case (see Appendix A.1). Define the Hilbert scale , determined by the multiplication operator . Then, for some , define the measurable functions , so that continuously, and are dual of each other. One has indeed and , which implies duality. Thus is a reproducing pair with , where is an upper semi-frame and a lower semi-frame.
In this case, one can compute the operators explicitly. For all , the definition (37) reads as
that is, or . However, since the weight is invertible, runs over the whole of whenever g runs over . Hence means that , which implies , since the duality between and is separating. The same reasoning yields . Therefore and .
Similar examples concerning spaces of sequences may be found in [23] (Section 5.2), possibly more general, in the sense that the space is no longer a Hilbert scale, but a genuine LHS.
6.3. A Reproducing Pair with Two PIP-Spaces
An easy example may be derived from the previous one. For the target space , we keep the same Hilbert scale (A2) built on the powers of the self-adjoint operator . For the initial space Y, we take a similar Hilbert scale (A2), but around , instead of . Thus for each , we have
Hence, means that
Given two positive integers , we take for analyzing functions , where is again the reproducing function of . Then we have:
- and ; for instance,
- .
In conclusion, as for the previous example, is a reproducing pair with , where is an upper semi-frame and a lower semi-frame.
Here too, one can compute the operators explicitly. For all , the definition (37) reads as
that is, or . Similarly .
As compared with the general scheme of Definition 1, we have taken . This means, in particular, that the condition is satisfied, as expected for a reproducing pair.
Author Contributions
Both authors, Antoine and Trapani, contributed equally.
Acknowledgments
We thank the referees for their remarks and suggestions, that have significantly clarified and improved the article.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A. Lattices of Banach or Hilbert Spaces and Operators on Them
Appendix A.1. Lattices of Banach or Hilbert Spaces
For the convenience of the reader, we summarize in this Appendix the basic facts concerning pip-spaces and operators on them. However, we will restrict the discussion to the simpler case of a lattice of Banach spaces (LBS) or Hilbert spaces (LHS). Further information may be found in our monograph [7] or the review paper [18].
Let thus be a family of Hilbert spaces or reflexive Banach spaces, partially ordered by inclusion. Then generates an involutive lattice , indexed by J, through the operations :
| . involution: | , the conjugate dual of | ||
| . infimum: | |||
| . supremum: | . |
It turns out that both and are Hilbert spaces, resp. reflexive Banach spaces, under appropriate norms (the so-called projective, resp. inductive norms). Clearly the index set J is also an involutive lattice, isomorphic to by the correspondence .
Assume that the following conditions are satisfied:
- (i)
- contains a unique self-dual, Hilbert subspace .
- (ii)
- for every , the norm on is the conjugate of the norm on .
Then the pip-space is called a LBS, resp. a LHS. Notice that denotes a family of spaces, whereas denotes the associated pip-space.
In addition to the family , it is convenient to consider the two vector spaces V and defined as
These two spaces themselves usually do not belong to . According to the general theory of pip-spaces [7], V is the algebraic inductive limit of the ’s and is the projective limit of the ’s.
We say that two vectors are compatible (This notion is the basis of the theory of pip-spaces [7], it should not be confused with that of Definition 2 !) if there exists . Then a partial inner product on V is a Hermitian form defined exactly on compatible pairs of vectors. In particular, the partial inner product coincides with the inner product of on the latter. A partial inner product space (pip-space) is a vector space V equipped with a partial inner product. Clearly LBSs and LHSs are particular cases of pip-spaces.
From now on, we will assume that our pip-space is nondegenerate, that is, for all implies . As a consequence, and every couple are a dual pair in the sense of topological vector spaces [31]. In particular, the original norm topology on coincides with its Mackey topology , so that indeed its conjugate dual is . Then, implies , and the embedding operator is continuous and has dense range. In particular, is dense in every . Throughout we also assume the partial inner product to be positive definite, whenever .
A standard, albeit trivial, example is that of a Rigged Hilbert space (RHS) (it is trivial because the lattice contains only three elements).
Familiar concrete examples of pip-spaces are sequence spaces, with , the space of all complex sequences , and spaces of locally integrable functions with , the space of Lebesgue measurable functions, integrable over compact subsets.
Among LBSs, the simplest example is that of a chain of reflexive Banach spaces. The prototype is the chain of Lebesgue spaces over the interval [0, 1].
As for a LHS, the simplest example is the Hilbert scale generated by a self-adjoint operator in a Hilbert space . Let be , the domain of , equipped with the graph norm , for or , and (conjugate dual):
Note that here the index n may be integer or real, the link between the two cases being established by the spectral theorem for self-adjoint operators. Here again the inner product of extends to each pair , but on it yields only a partial inner product. For standard examples, take and the following operators:
- .
- yields the Fourier transform of the Sobolev spaces .
- .
- yields the Sobolev spaces .
- .
- yields the harmonic oscillator representation of the Schwartz space of smooth functions of fast decay and its conjugate dual , the space of of tempered distributions.
Appendix A.2. Operators on LBSs and LHSs
Let be an LHS or an LBS. Then an operator on is a map A from a subset into V, such that
- (i)
- , where is a nonempty subset of J;
- (ii)
- For every , there exists such that the restriction of A to is a continuous linear map into (we denote this restriction by ;
- (iii)
- A has no proper extension satisfying (i) and (ii).
We denote by Op the set of all operators on . The continuous linear operator is called a representative of A. The properties of A are conveniently described by the set of all pairs such that A maps continuously into Thus the operator A may be identified with the collection of its representatives,
It is important to notice that an operator is uniquely determined by any of its representatives, in virtue of Property (iii): there are no extensions for pip-space operators.
If is a representative of the operator A, then so are , for any , where is a representative of the unit operator, and also , for any . Operators between an LHS/LBS into another one are defined in the same way. They are denoted as .
Although an operator may be identified with a separately continous sesquilinear form on , or a conjugate linear continuous map into V, it is more useful to keep also the algebraic operations on operators, namely:
- (i)
- Adjoint: every has a unique adjoint , defined bythat is, , where is the adjoint map of . Furthermore, one has for every : no extension is allowed, by the maximality condition (iii) of the definition.
- (ii)
- Partial multiplication: Let . The product is defined if and only if there is a continuous factorization through some :
Several classes of operators are of particular interest, for instance:
- (i)
- Symmetric operators, defined as those operators satisfying the relation , since these are the ones that may generate self-adjoint operators in the central Hilbert space [7] (Section 3.3).
- (ii)
- Invertible operators: A is invertible if it has at least one invertible representative; in that case, A has a unique inverse operator [28].
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