Approximative K-Atomic Decompositions and frames in Banach Spaces
Shah Jahan
Shah Jahan, Department of Mathematics,
University of Delhi, Delhi-110007, India
[email protected]
Abstract.
[L. Gavruta, Frames for Operators, Appl. comput. Harmon. Anal. 32(2012), 139-144] introduced a special kind of frames, named K-frames, where K is an operator, in Hilbert spaces, is significant in frame theory and has many applications. In this paper, first of all, we have introduced the notion of approximative K-atomic decomposition in Banach spaces. We gave two characterizations regarding the existence of approximative K-atomic decompositions in Banach spaces. Also some results on the existence of approximative K-atomic decompositions are obtained. We discuss several methods to construct approximative K-atomic decomposition for Banach Spaces. Further, approximative Xdβ-frame and approximative Xdβ-Bessel sequence are introduced and studied. Two necessary conditions are given under which an approximative Xdβ-Bessel sequence and approximative Xdβ-frame give rise to a bounded operator with respect to which there is an approximative K-atomic decomposition. Examples and counter examples are provided to support our concept. Finally, a possible application is given.
Key words and phrases:
Frames; K-frames; Atomic decomposition; K-Atomic decomposition; Xdβ-Bessel sequence ; Xdβ-frames
2010 Mathematics Subject Classification:
42A38, 42C15, 42C30, 46B15
1. Introduction and Preliminaries
Fourier transform has been a major tool in analysis for over a century. It has a serious lacking for signal analysis in which it hides in its phase information concerning the moment of emission and duration of a signal. What actually needed was a localized time frequency representation which has this information encoded in it. In 1946, Dennis Gabor [13] filled this gap and formulated a fundamental approach to signal decomposition in terms of elementary signals. On the basis of this development, in 1952, Duffin and Schaeffer [9] introduced frames for Hilbert spaces to study some deep problems in non-harmonic Fourier series. In fact, they abstracted the fundamental notion of Gabor for studying signal processing.
Let H be a real (or complex) separable Hilbert space with inner product β¨.,.β©. A countable sequence {fnβ}βH is called a frame for the Hilbert space H, if there exist positive constants A,Β B>0 such that
[TABLE]
The positive numbers A and B are called the lower and upper frame bounds of the frame, respectively. These bounds are not unique. The inequality in (1.1) is called the frame inequality of the frame. If {fnβ} is a frame for H then the following operators are associated with it.
- (a)
Pre-frame operator T:l2(N)βΆH is defined as T{cnβ}n=1ββ=k=1βββcnβfnβ,Β Β {cnβ}n=1βββl2(N).
2. (b)
Analysis operator Tβ:HβΆl2(N),Tβ={β¨f,fkββ©}k=1ββΒ Β Β fβH.
3. (c)
Frame operator S=TTβ=:HβΆH,Β Β Sfβ=k=1ββββ¨f,fkββ©fkβ,Β Β fβH. The frame S is bounded, linear and invertible on H. Thus, a frame for H allows each vector in H to be written as a linear combination of the elements in the frame, but the linear independence between the elements is not required; i.e for each vector fβH we have,
[TABLE]
For more details related to frame and Riesz bases in Hilbert spaces, one may refer to [4, 7]. These ideas did not generate much interest outside of non-harmonic Fourier series and signal processing for more than three decades until Daubechies et al. [8] reintroduced frames. After this landmark paper the theory of frames begin to be studied widely and found many applications to wavelet and Gabor transforms in which frames played an important role. Feichtinger and GrΓΆcheing [11] extended the idea of Hilbert frames to Banach spaces and called it atomic decomposition. A more general concept called Banach frame was introduced by GrΓΆcheing [15] and were further studied in [19, 31]. Banach frames were developed for the theory of frames in the context of Gabor and Wavelet analysis. Christensen and Heil [6] studied some perturbation results for Banach frames and atomic decompositions.
In particular, frames are widely used in sampling theory in [1] amounts to the construction of Banach frames consisting of reproducing kernals for a large class of shift invariant spaces. Aldroubi et al. [2] used Banach frames in various irregular sampling problems. Elder and Forney [10] used tight frames for quantum measurement. GrΓΆchenig [16] emphasised that localization of a frame is a necessary condition for its extension to a Banach frame for the associated Banach spaces. He also observed that localized frames are universal Banach frames for the associated family of Banach spaces.
Fornasier [12] studied Banach frames for Ξ±-modulation spaces. In fact, he gave a Banach frame characterization for the Ξ±-modulation spaces. Shah et.al [18] defined and studied Banach frames to a new geometric notation; in fact they gave a sufficient condition and a necessary condition for a cone associated with a Banach frame to be a generating cone.
Casazza et al. [5] studied Xdβ-frames and Xdβ-Bessel sequences in Banach spaces. Stoeva [27] gave some perturbation results for Xdβ-frames and atomic decompositions. Kaushik and Sharma [20] studied approximative atomic decompositions in Banach spaces. For further studies related to approximative frame one may refer [17, 21, 25]. Gavruta [14] introduced and studied atomic system for an operator K and the notion of K-frame in a Hilbert space. Xiao et al. [30] discussed relationship between K-frames and ordinary frames in Hilbert spaces. Poumai and Jahan [23] introduced K-atomic decompositions in Banach spaces.
outline of the paper.
In this paper, we have introduced the notion of approximative K-atomic decomposition in Banach spaces. We gave two characterizations regarding the existence of approximative K-atomic decompositions in Banach spaces. Also some results on the existence of approximative K-atomic decompositions are obtained. We discuss several methods to construct approximative K-atomic decomposition for Banach Spaces. Further, approximative Xdβ-frame and approximative Xdβ-Bessel sequence are introduced and studied. Two necessary conditions are given under which an approximative Xdβ-Bessel sequence and approximative Xdβ-frame give rise to bounded operators with respect to which there is an approximative K-atomic decomposition. Examples and counter examples are provided to support our concept of approximative K-atomic decomposition. Finally, we gave a possible application of our work.
Next we give some basic notations. Throughout this paper, X will denote a separable Banach space over the scalar field K(R or C), Xβ the dual space of X, Xdβ a BK-space and L(X,Y) will denote the space of all bounded linear operators from X into Y. For TβL(X), Tβ denotes the adjoint of T, Ο:XβΆXββ is the natural canonical projection from X onto Xββ. Also Tβ denote the pseudo inverse of the operator T. Note that TTβ f=f for all fβR(K). Throughout R(K) is closed.
Definition 1.1*.*
[15]Let X be a Banach space and Xdβ be a BK-space. A sequence (xnβ,fnβ)({xnβ}βX,{fnβ}βXβ) is called an atomic decomposition for X with respect to Xdβ if the following statements hold:
- (a)
{fnβ(x)}βXdβ, for all xβΒ X.
2. (b)
There exist constants A and B with 0<Aβ€B<β such that
[TABLE]
3. (c)
x=n=1βββfnβ(x)xnβ,Β Β for all xβX.
Next, we state some lemmas which we will use in the subsequent results.
Lemma 1.2**.**
[28, 31*]*Let X, Y be Banach spaces and T:XβΆY be a bounded linear operator. Then, the following conditions are equivalent:
- (a)
There exist two continuous projection operators P:XβX and Q:YβY such that
[TABLE]
2. (b)
T* has a pseudo inverse operator Tβ .*
If two continuous projection operators P:XβX and Q:YβY satisfies (2.3), then there exists a pseudo inverse operator Tβ of T such that Tβ T=IXββP Β and Β TTβ =Q, where IXβ is the identity operator on X.
Lemma 1.3**.**
[3, 24*]*Let X be a Banach space. If TβL(X) has a generalized inverse SβL(X), then TS, ST are projections and TS(X)=T(X) and ST(X)=S(X).
Lemma 1.4**.**
[20, 26]** Let X be a Banach space and {fnβ}βXβ be a sequence such that {xβX:fnβ(x)=0,forΒ allΒ nβN}={0}. Then X is linearly isometric to the Banach space Xdβ={{fnβ(x)}:xβX}, where the norm is given by β₯{fnβ(x)}β₯Xdββ=β₯xβ₯Xβ, xβX.
2. Main Results
Poumai and Jahan [23] defined and studied K-atomic decomposition as a generalization of K-frames in Banach spaces. Here we shall extend this study further and introduced the concept of approximative K-atomic decomposition in Banach spaces and obtained new and interesting results. We start this section with the following definition of approximative K-Atomic decomposition:
Definition 2.1*.*
Let X be a Banach Space, {xnβ}βX,{hn,iβ}nβNi=1,2,3,...,mnββββXβ, where {mnβ} is an increasing sequence of positive integer and KβL(X). A pair ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is called an approximative K-atomic decomposition for X with respect to Xdβ, if the following statements holds:
- (a)
{hn,iβ(x)}nβNi=1,2,3,...,mnββββXdβ, for all xβX.
2. (b)
There exist constants A and B with 0<Aβ€B<β such that
[TABLE]
3. (c)
nββlimβi=1βmnββhn,iβ(x)xiβ converges for all xβX and
K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ.
The constants A and B are called lower and upper bounds of the approximative K-atomic decomposition ({xnβ},{hn,iβ}i=1,2,3,...,mnββ).
Observations*.*
If ({xnβ},{fnβ}) is a K-atomic decomposition for X with respect to Xdβ, then for hn,iβ=fiβ,i=1,2,...,n,nβN, ({xnβ},{hn,iβ}) is an approximative K-atomic decomposition for X with respect to some associated Banach space Xdβ.
Remark 2.2*.*
Let (xnβ,hn,iβ) be an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and B.
(I)
If K=IXβ, then (xnβ,hn,iβ) is an approximative atomic decomposition for X with respect to Xdβ with bounds A and B.
(II)
If K is invertible, then (Kβ1(xnβ),hn,iβ) is an approximative atomic decomposition for X with respect to Xdβ.
In the following example, we show the existence of approximative K-atomic decomposition for a Banach space X with respect to an associated BK space Xdβ .
Example 2.3*.*
Let X be a Banach Space. Let{xnβ}βX, {hn,iβ}βXβ such that nββlimβi=1βmnββhn,iβ(x)xnβ converges for all xβX and xnβξ =0, for all nβN. Also, let Xdβ={{hn,iβ}β£nββlimβi=1βmnββhn,iβxiβΒ \mboxconverges}. Then Xdβ is a BK-space with norm β₯{hn,iβ(x)}β₯Xdββ=1β€n<βsupββ₯i=1βnβhn,iβxiββ₯. Define an operator as T:XdββΆX as T{hn,iβ}=nββlimβi=1βmnββhn,iβxiβ and define S:XβΆXdβ as S(x)={hn,iβ(x)},Β xβX. Take K=TS. Then K:XβΆX is such that K(x)=TS(x)=nββlimβi=1βmnββhn,iβ(x)xiβ, for all xβX,Β i=1,2,...,n,Β nβN. Clearly, {hn,iβ(x)}βXdβ and
[TABLE]
where C=1β€n<βsupββ₯Snββ₯ and Snβ(x)=nββlimβi=1βmnββhn,iβ(x)xiβ.
Hence, (xnβ,hn,iβ) is an approximative K-atomic decomposition for X with respect to Xdβ.
In the following result, we give the characterization regarding the existence of approximative K-atomic decompositions in Banach spaces.
Theorem 2.4**.**
Let KβL(X) with Kξ =0. Then a Banach space X has an approximative K-atomic decomposition if and only if there exists a sequence {viβ}βB(X) of finite rank endomorphism such that K(x)=i=1βnβviβ(x),Β Β xβX.
Proof.
Let {xnβ}βX and {hn,iβ}nβNi=1,2,3,...,mnββββXβ, where {mnβ} is an increasing sequence of positive integer such that ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative K-atomic decomposition for X with respect to Xdβ. Define
[TABLE]
Then for each nβN and xβX, Snβ(x) is a well defined continuous linear mapping on X such that nββlimβSnβ(x)=x,Β Β xβX. Also by uniform boundedness principle we have 1β€nβ€βsupββ₯Snβ(x)β₯<β.
Assume that v1β=S1β,Β Β v2nβ=v2n+1β=21β(Sn+1ββSnβ),nβN. Now, we compute
[TABLE]
Therefore, nββlimββi=1nβviβ(x)=K(X).
Conversely assume that there exists a sequence of finite rank endomorphism {Snβ}βL(X) such that nββlimβSnβ(x)=K(x),Β Β xβX. Then, each Snβ(x) is of finite rank, there exist a sequence {yn,iβ}i=mnβ1β+1mnβββX and a total sequence of row finite matrix of functionals {gn,iβ}i=mnβ1β+1mnβββXβ such that
[TABLE]
Define sequences {xnβ}βX and {hn,iβ}nβNi=1,2,3,...,mnββββXβ, where {mnβ} is an increasing sequence of positive integers, by
[TABLE]
and
[TABLE]
Then xnβξ =0, so for each xβX and nβN, we get
[TABLE]
Let xβX be such that hn,iβ(x)=0,\mboxforallΒ i=1,2,...mnβ,Β Β nβN. Then by equation (2.4) K(x)=0. Thus by Lemma 1.4 there exist an associated Banach space Xdβ={{hn,iβ}nβNi=1,2,3,...,mnβββ,xβX} with norm given by β₯{hn,iβ}nβNi=1,2,3,...,mnββββ₯Xdββ=β₯xβ₯Xβ,Β Β \mboxforallΒ xβX. Hence ({hn,iβ},{xnβ}) is an approximative K-atomic decomposition for X with respect to Xdβ.
β
Next, we give an example of an approximative K-atomic decomposition for X which is not an approximative atomic decomposition for X.
Example 2.5*.*
Let X=c0βΒ andΒ Xdβ=lββ. Let {xnβ}βX be the sequence of standard unit vectors in X and {hn,iβ}βXβ be such that for x={Ξ±nβ}βX,hn,1β(x)=0,hn,2β(x)=Ξ±2β,...,hn,iβ(x)=Ξ±nβ,.... It is clear that nββlimβi=1βmnββhn,iβ(x)xiβ converges for xβX. Define K:XβΆX by K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ , xβX. Then {hn,iβ(x)}βXdβ is such that ({xnβ},{hn,iβ(x)}) is an approximative K-atomic decomposition for X with respect to Xdβ. But ({xnβ},{hn,iβ}) is not an approximative atomic decomposition for X.
Next, we give various methods for the construction of approximative K-atomic decompositions for X.
Theorem 2.6**.**
Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative atomic decomposition for X with respect to Xdβ with bounds A and B. Let KβL(X) with Kξ =0. Then ({Kxnβ},{hn,iβ}nβNi=1,2,3,...,mnββ) is an approximative K-atomic decomposition for X with respect to Xdβ with bounds β₯Kβ₯Aβ and B.
Proof.
Since ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative atomic decomposition for X with respect to Xdβ with bounds A and B. So for each xβX, we have x=nββlimβi=1βmnββhn,iβ(x)xiβ. This implies K(x)=nββlimβi=1βmnββhn,iβ(x)K(xiβ).
Also, we have β₯K(x)β₯XβΒ β€Β β₯Kβ₯β₯xβ₯Xβ, for all xβX. This gives
[TABLE]
β
Theorem 2.7**.**
Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative atomic decomposition for X with respect to Xdβ with bounds A and B. Let KβL(X) with Kξ =0. Then ({xnβ},{Kβhn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and Bβ₯Kβ₯.
Proof.
Can be easily proved.
β
Theorem 2.8**.**
Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and B and let TβL(X) with Tξ =0. Then ({Txnβ},{hn,iβ}) is an approximative TK-atomic decomposition for X with respect to Xdβ with bounds β₯Tβ₯Aβ and B.
Proof.
Construction of proof is similar to theorem 2.6.
β
Theorem 2.9**.**
Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and B and let TβL(X) with β₯Tβ₯ξ =0 Then ({xnβ},{Tβhn,iβ}) is an approximative KT-atomic decomposition for X with respect to Xdβ with bounds A and Bβ₯Tβ₯.
Proof.
Obvious
β
Theorem 2.10**.**
If ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative K-atomic decomposition for X with respect to Xdβ and K has pseudo inverse Kβ , then there exists {gn,iβ}βXβ such that ({xnβ},{gn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and Bβ₯Kβ₯2
Proof.
Since ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative K-atomic decomposition for X with respect to Xdβ, then for each xβX we have
[TABLE]
Also, for each xβX, we have
[TABLE]
For each nβN, define gn,iβ=(Kβ K)β(hn,iβ). Then
[TABLE]
and
[TABLE]
Hence, we conclude that ({xnβ},{gn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ.
β
3. Approximative Xdβ-frame
Casazza et al. [5] defined and studied Xdβ-Bessel sequences and Xdβ-frames in Banach spaces. Later on Stoeva [27] studied perturbation of Xdβ-Bessel sequences, Xdβ-frames, atomic decomposition and Xdβ-Riesz bases in separable Banach spaces. We have generalized this concept and defined approximative Xdβ-Bessel sequences and approximative Xdβ-frames in Banach spaces. We begin this section with the following definitions:
Definition 3.1*.*
A sequence {hn,iβ}nβNi=1,2,3,...,mnββββXβ, where {mnβ} is an increasing sequence of positive integers, is called an approximative Xdβ-frame for X if
- (a)
{hn,iβ(x)}nβNi=1,2,3,...,mnββββXdβ, for all xβX.
2. (b)
There exist constants A and B with 0<Aβ€B<β such that
[TABLE]
The constants A and B are called approximative Xdβ-frame bounds.
If atleast (a) and the upper bound condition in (3.5) are satisfied, then {hn,iβ} is called an approximative Xdβ-Bessel sequence for X.
One may note that if {fnβ} is an Xdβ-frame for X, then for {hn,iβ}=fiβ,Β i=1,2,3,...,n;Β nβN, {hn,iβ} is an approximative Xdβ-frame for X. Also, note that if {fnβ} is an Xdβ-Bessel sequence for X, then for {hn,iβ}=fiβ,Β i=1,2,3,...,n;Β nβN, {hn,iβ} is an approximative Xdβ-Bessel sequence for X.
In the next two results, we give necessary conditions under which an approximative Xdβ-frame gives rise to a bounded operator K with respect to which there is an approximative K-atomic decomposition for X.
Theorem 3.2**.**
Let {hn,iβ}nβNi=1,2,3,...,mnββββXβ be an approximative Xdβ-frame for X with bounds A and B. Let {xnβ}βX with 1β€n<βsupββ₯xnββ₯<β and let nββlimβi=1βmnβββ£hn,iβ(x)β£<β, for all xβX. Then there exists an operator KβL(X) such that ({xnβ},{hn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ.
Proof.
Since {hn,iβ}nβNi=1,2,3,...,mnββββXβ is an approximative Xdβ-frame for X with 1β€n<βsupββ₯xnββ₯<β and nββlimβi=1βmnβββ£hn,iβ(x)β£<β. Then, by Theorem 2.4, we have nββlimβi=1βmnββhn,iβ(x)xiβ exist for all xβX,Β nβN.
Define K:XβΆX by K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ, xβX. Then K is a bounded linear operator such that
[TABLE]
where C=1β€n<βsupβi=1βmnββhn,iβ(x)xiβ. Thus
[TABLE]
Hence, ({xnβ},{hn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ with bounds CAβ and B.
β
Theorem 3.3**.**
Let {hn,iβ}nβNi=1,2,3,...,mnββββXβ be an approximative Xdβ-frame with bounds A,Β B and let {xnβ}βX. Let T:XdββΆX given by T({hn,iβ})=nββlimβi=1βmnββhn,iβxiβ be a well defined operator. Then, there exists a linear operator KβL(X) such that ({xnβ},{hn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ.
Proof.
Define U:XβΆXdβ by U(x)={hn,iβ(x)}, xβX. Then U is well defined and β₯Uβ₯β€B. Take K=TU. Then K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ,Β xβX. Therefore, by uniform boundedness principle, we have
[TABLE]
where C=1β€n<βsupββ₯i=1βmnββhn,iβ(x)xiββ₯Xβ. Thus, we have
[TABLE]
Hence ({xnβ},{hn,iβ}) is an approximative K-atomic decomposition for X with respect to Xdβ with bounds CAβ and B.
β
Next, we give the existence of an approximative K-atomic decomposition from an approximative Xdβ Bessel sequence.
Theorem 3.4**.**
Let X be a reflexive Banach space and Xdβ be a BK-space which has a sequence of canonical unit vectors {enβ} as a basis. Let {hn,iβ}nβNi=1,2,3,...,mnββββXβ be an approximative Xdβ-Bessel sequence with bound B and let {xnβ}βX. If {h(xnβ)}β(Xdβ)β for all hβXβ, then there exists a bounded linear operator KβL(X) such that ({xnβ},Β {hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative K-atomic decomposition for X with respect to Xdβ.
Proof.
Clearly U:XβΆXdβ given by U(x)={hn,iβ(x)},Β xβX is well defined. Define a map R:XββΆ(Xdβ)β by R(h)={h(xnβ)},Β xβX. Then, its adjoint Rβ:(Xdβ)βββΆXββ is given by Rβ(ejβ)(h)=ejβ(R(h))=h(xjβ). Let T=(Rβ)β£Xdββ and {hn,iβ}βXdβ. Then
[TABLE]
But {hn,iβ(x)}βXdβ. So T({hn,iβ(x)})=nββlimβi=1βmnββhn,iβ(x)xiβ.
Take K=TU.
Then KβL(X)Β andΒ K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ.
Moreover, T is a bounded linear operator such that β₯K(x)β₯β€β₯Tβ₯β₯{hn,iβ(x)}β₯.
Hence
[TABLE]
β
Next, we construct an approximative Kβ-atomic decomposition for Xβ from a given approximative K-atomic decomposition for X.
Theorem 3.5**.**
Let Xdβ be a BK-space with dual (Xdβ)β and let Xdβ and (Xdβ)β have sequences of canonical unit vectors {enβ}Β andΒ Β {vnβ} respectively as bases. Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative K-atomic decomposition for X with respect to Xdβ. Let S:XdββΆX given by S({hn,iβ})=nββlimβi=1βmnββhn,iβxiβ be a well defined mapping. Then, ({hn,iβ}nβNi=1,2,3,...,mnβββ,Ο(xnβ)) is an approximative Kβ-atomic decomposition for Xβ with respect to (Xdβ)β.
Proof.
Since ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative K-atomic decomposition for X with respect to Xdβ, so for each xβX, K(x)=nββlimβi=1βmnββhn,iβ(x)xiβ. Thus
h(K(x))=nββlimβi=1βmnββhn,iβ(x)h(xiβ). Therefore, by Theorem 2.4 we have nββlimβi=1βmnββh(xiβ)hn,iβ exist for all hβXβ. Also, for xβX, we compute
[TABLE]
This gives Kβ(h)=nββlimβi=1βmnββh(xiβ)hn,iβ, for hβXβ. Note that
Sβ(h)(ejβ)=h(S(ejβ))=h(xjβ),hβXβ. So, Sβ(h)={h(xnβ)} and {h(xnβ)}={h(S(enβ))}β(Xdβ)β,hβXβ.
Also
[TABLE]
Define R:XβΆXdβ by R(x)={hn,iβ(x)},xβX. Then, Rβ(vjβ)(x)=vjβ(R(x))=hj,iβ(x), xβX. So, Rβ(vjβ)=hj,iβ, for all jβN and for {gn,iβ}β(Xdβ)β we have
[TABLE]
Therefore, we have
[TABLE]
Note that, Kβ=RβSβ and so
[TABLE]
This gives
[TABLE]
Hence, ({hn,iβ}nβNi=1,2,3,...,mnβββ,Ο(xnβ)) is an approximative Kβ-atomic decomposition for Xβ with respect to (Xdβ)β.
β
Next, we give the following result characterizing the class of approximative K-atomic decompositions.
Theorem 3.6**.**
Let ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) be an approximative K-atomic decomposition for X with respect to Xdβ with bounds A and B. Let T:XdββΆX given by T({hn,iβ})=nββlimβi=1βmnββhn,iβxiβ is well defined for {hn,iβ}βXdβ and let U:XβΆXdβ be the mapping given by U(x)={hn,iβ(x)}. If K is invertible, then the following statements are equivalent.
- (a)
T* is the pseudo inverse of U.*
2. (b)
({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ)* is an approximative atomic decomposition for X with respect to Xdβ.*
3. (c)
T* is a linear extension of Uβ1:U(X)βΆX.*
4. (d)
U(X)* is a complemented subspace of Xdβ.*
5. (e)
KerT* is a complemented subspace of Xdβ and T is surjective.*
Proof.
(a)β(b)
By hypothesis, {xβX:hn,iβ(x)=0,Β forΒ allΒ nβN}={0}. So, KerU={0}. Since T is the pseudo inverse of U, by Lemma 1.2 there exists a continuous projection operator ΞΈ:XβΆX such that TU=IXββΞΈ and kerU=ΞΈ(X). Thus, for each xβX, we have
[TABLE]
Hence, for every xβX, nββlimβi=1βmnββhn,iβ(x)xiβ=x.
(b)\Rightarrow(a)\For xβX, we have
[TABLE]
Hence, UTU=U.
(c)\Rightarrow(b)\ \If T is a linear extension of Uβ1:U(X)βΆX, then TU:XβΆX is the identity map on X. So, TU(x)=x and nββlimβi=1βmnββhn,iβ(x)xiβ=x.
(c)\Rightarrow(a)\Obvious, since UTU=UIXβ=U.
(d)β(b) Β Suppose Xdβ=U(X)βG, where G is a closed subspace of Xdβ. Let P be a projection of Xdβ onto U(X) along G.
Then, P({hn,iβ})={gn,iβ(nββlimβi=1βmnββhn,iβxiβ)}, for all {hn,iβ}βXdβ. Therefore
[TABLE]
This gives, T=Uβ1βP and
[TABLE]
Hence, x=nββlimβi=1βmnββhn,iβ(x)xiβ, for all xβX.
(b)β(d) Β Obvious.
(e)β(b) Let Xdβ=kerTβM, where M is a closed subspace of Xdβ. Take Ξ₯=kerTβU(X). Let Q:XdββΆM be a projection from Xdβ onto M along kerT. Define L:XdββΆΞ₯ by L(Ξ±)=(Ξ±βQ(Ξ±),UT(Ξ±)), for Ξ±={hn,iβ}βXdβ. Let L(Ξ±)=0. This gives Q(Ξ±)=Ξ±. So Ξ±βM. Let UT(Ξ±)=0. Then
[TABLE]
This gives nββlimβi=1βmnββhn,iβxiβ=0 and so, Ξ±βkerT. Thus, Ξ±βkerTβ©M={0}. Hence, L is one-one.
Let (Ξ±0β,U(x))βkerTβU(X), for Ξ±0ββkerU and U(x)βU(X).
Since, T is onto, for each xβX, there exists Ξ²βXdβ such that T(Ξ²) = x and this gives UT(Ξ²)=U(x). Take Ξ±=Ξ±0β+Q(Ξ²). Then Q(Ξ±)=Q(Ξ±0β)+Q2(Ξ²)=Q(Ξ²) and Ξ±0β=Ξ±βQ(Ξ±). Also, we have
[TABLE]
Thus L(Ξ±)=(Ξ±0β,UT(x))
and L is an isomorphism from Xdβ onto Ξ₯. So, there is a projection P=UT:XdββΆU(X) onto U(X) along kerT. This gives
[TABLE]
Finally, we compute
[TABLE]
Therefore, ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative atomic decomposition for X with respect to Xdβ.
(b)β(e) Obvious.
β
In the following result, we prove a duality type approximative K-atomic decomposition for X.
Theorem 3.7**.**
Let Xdβ be a reflexive BK-space with its dual (Xdβ)β and let sequences of canonical unit vectors {enβ}Β andΒ {vnβ} be bases for Xdβ and (Xdβ)β, respectively. Let ({hn,iβ}nβNi=1,2,3,...,mnβββ,Ο(xnβ)) be an approximative K-atomic decomposition for Xβ with respect to (Xdβ)β. If S:(Xdβ)ββΆXβ given by S({diβ})=nββlimβi=1βmnββdiβhn,iβ is well defined for {diβ}βXdββ, then there exists a linear operator LβL(X) such that ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative L-atomic decomposition for X with respect to Xdβ.
Proof.
Since ({hn,iβ}nβNi=1,2,3,...,mnβββ,Ο(xnβ)) is an approximative K-atomic decomposition for Xβ with respect to (Xdβ)β.
For hβXβ, we have K(h)=nββlimβi=1βmnββh(xiβ)hn,iβ. Also, by Theorem 2.4
we have nββlimβi=1βmnββhn,iβ(x)xiβ exist, for all xβX.
DefineL:XβΆX by Β L(x)=nββlimβi=1βmnββhn,iβ(x)xiβ,Β xβX. Note that S(vnβ)=hn,iβ,Β nβN and for xβX, the linear bounded operator Sβ:XβββΆ(Xdβ)ββ satisfies
[TABLE]
So, {hn,iβ(x)} is identified with Sβ(Ο(x))β(Xdβ)ββ=Xdβ. Further, we have
[TABLE]
Letting U=Sββ£Xβ, we have U(x) ={hn,iβ(x)} and β₯Uβ₯β€β₯Sβ₯.
Define R:XββΆ(Xdβ)β by R(f)={h(xnβ)},hβXβ. Then
[TABLE]
So, Rβ(ejβ)=xjβ,\mboxforallΒ jβN. Take T=(Rβ)β£Xdββ. Then, for {hn,iβ}βXdβ we compute
[TABLE]
Thus, TU(x)=nββlimβi=1βmnββhn,iβ(x)xiβ, for all xβX and this gives TU=L on X. Therefore, β₯Tβ₯1ββ₯L(x)β₯Xββ€β₯{hn,iβ(x)}β₯Xdββ. Then
[TABLE]
Hence, ({xnβ},{hn,iβ}nβNi=1,2,3,...,mnβββ) is an approximative L-atomic decomposition for X with respect to Xdβ.
β
4. Possible Application
One of the most important device in modern world is digital camera. In our notation a digital picture is a two-dimensional sequence, {hnmβ}. So, it can be seen either as an infinite length sequence with a finite number of non-zeros samples; that is
{hnmβ},Β Β n,mβZ, or as a sequence with domain nβ{0,1,2,...,Nβ1}, mβ{0,1,2,...,Mβ1}, can be expressed as a matrix:
[TABLE]
where each elements hnmβ is called a pixel and the image has NM pixels. In real life for hn,mβ to represent colour image, it must have more than one component, usually, red, green and blue components are used(RGB colour space).