AND LIZORKIN-TRIEBEL SPACES
DOUADI DRIHEM AND MADANI MOUSSAI
Received 1 February 2005; Revised 22 February 2006; Accepted 4 April 2006
Under some sufficient conditions satisfied byF-space of Lizorkin and Triebel andB-space of Besov, we prove some embeddings of typesF·BF,F·FF, andB·BB.
Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
1. Introduction and preparations
In Besov spaces and Lizorkin-Triebel spaces, this paper is concerned with proving some embeddings of the form
F·B F, F·F F, B·B B, (1.1)
whereF andB, with three indices, will denote the Lizorkin-Triebel spaceFsp,q and the Besov spaceBsp,q, respectively. The different embeddings obtained here are under certain restrictions on the parameters.
In this introduction, we will recall the definition of some spaces and some necessary tools. In Sections2and3, we give the first contribution of this work. The theorems of Section 2will treat the caseF·BF where the first theorem is a generalization of the results of Franke [4, Section 3.2, Theorem 1, Section 3.4, Corollary 1] and Marschall [7].
The second theorem is in the sense of Johnsen’s works (see [5]).Section 3will contain a treatment of the embeddings of the typesF·FF andB·BBwhich presents an improvement of [3].
In the sense of [5, Theorems 6.5, 6.11], some limit cases are considered inSection 4, which constitute the second contribution of this paper.Section 5is an application of our results to the continuity of pseudodifferential operators on Lizorkin-Triebel spaces.
We will work on the Euclidean spaceRn. If f ∈, the Fourier transform is defined by the formula
Ᏺf(ξ)= f(ξ)=
Rn f(x)e−ix·ξdx ξ∈Rn
(1.2)
Hindawi Publishing Corporation
International Journal of Mathematics and Mathematical Sciences Volume 2006, Article ID 76182, Pages1–18
DOI10.1155/IJMMS/2006/76182
andᏲ−1f denotes the inverse Fourier transform of f; as usualᏲandᏲ−1are extended fromto.
Consider a partition of unity ψ(ξ) +
∞ j=1
ϕ2−jξ=1 ξ∈Rn
, (1.3)
whereϕ,ψ∈C∞ are positive functions such that suppϕ⊂ {ξ∈Rn: 1≤ |ξ| ≤3} and suppψ⊂ {ξ∈Rn:|ξ| ≤3}. We define the convolution operatorsQj andΔkby the fol- lowing:
Qjf =Ᏺ−1ψ2−j·
∗f (j=1, 2,. . .), Δkf =Ᏺ−1ϕ2−k·
∗f (k=0, 1,. . .),
(1.4)
and we setQ0=Δ0. Thus we obtain the Littlewood-Paley decomposition f =∞
j=0Δjf (convergence in).
Let us now recall the definitions ofFp,qs andBsp,q, where the general references include [1,9–13].
Definition 1.1. Letγ >0,−∞< s <∞, 0< p <∞(resp., 0< p≤ ∞), and 0< q≤ ∞. The spaceLγp(qs) (resp.,sq(Lγp)) is the set of the sequences{fk}k∈N⊂Ssuch that suppfk⊂ {ξ∈Rn:|ξ|< γ2k}and
fk
k∈N|Lγp
qs= 2ksfk
k∈N|Lp
q<∞, resp., fkk∈N|qsLγp= 2ksfkk∈N|qLp<∞
.
(1.5)
Definition 1.2. (i) Let 0< p <∞, 0< q≤ ∞, and−∞< s <∞, then Fp,qs = f ∈: 2ksΔkfk∈N|Lp
q<∞
. (1.6)
(ii) Let 0< p,q≤ ∞, and−∞< s <∞, then
Bsp,q= f ∈: 2ksΔkfk∈N|qLp<∞
. (1.7)
Remark 1.3. We introduce the maximal function
Δ∗k,afx=sup
y∈Rn
Δkfx−y
1 +2k|y|a (1.8)
for allx∈Rn, f ∈,a >0, andk=0, 1,. . . .Then, inDefinition 1.2(i) (resp., (ii)), we can replace Δkf byΔ∗k,af witha >(n/min(p,q)) (resp., a > n/ p), (cf. see [13, Theo- rem 2.3.2]).
The product f ·gis defined by f ·g=lim
j→∞Qjf ·Qjg ∀f,g∈ (1.9) if the limit on the right-hand side exists in(see [10, Section 4.2]), and we have
Δk(f ·g)= ∞ j,=0
Δk
Δjg·Δf=
Πk,1+Πk,2+Πk,3
(f,g), (1.10) where
Πk,1(f,g)=ΔkΔkf·Qk+1g, Πk,2(f,g)=Δk
Qk+1f·Δkg,
Πk,3(f,g)=∞
j=k
Δk
Δjf ·Δjg, (1.11)
withΔk=k+4
j=k−2ΔjandΔk=k+1
j=k−1Δj.
In the below proofs of the different cases of type (1.1), written as G1·G2G3, to see f ·gbelongs toG3, (f ∈G1,g∈G2), it suffices to an estimate of terms of the form {Πk,i(f,g)}k∈N|Lγp(sq)and{Πk,i(f,g)}k∈N|sq(Lγp),i∈ {1, 2, 3}.
Now we recall some lemmas which are useful for us.
Lemma 1.4. (i) Let −∞< si<∞, 0< pi<∞(resp., 0< pi≤ ∞), and 0< qi≤ ∞(with i=0, 1). If
s0> s1, p0=p1, (1.12)
or
s0≥s1, s0− n
p0 =s1− n p1
q0≤q1for Besov space, (1.13)
then it holds
Fsp00,q0 Fps11,q1
resp.,Bsp00,q0 Bsp11,q1
. (1.14)
(ii) Let−∞< s,si<∞, 0< p, pi<∞, and 0< q,qi≤ ∞(withi=0, 1) such thats0− n/ p0=s−n/ p=s1−n/ p1. If
s0> s > s1, q0≤p≤q1, (1.15) or
s0=s=s1, q0≤min(p,q), q1≥max(p,q), (1.16) then it holds
Bsp00,q0 Fsp,q Bsp11,q1. (1.17)
(iii) Let−∞< s <∞, 0< p <∞(resp., 0< p≤ ∞), and 0< q≤ ∞. If s >n
p, (1.18)
or
s=n
p, 0< p≤1 (resp., 0< q≤1), (1.19) then it holds
Fsp,q L∞ resp.,Bsp,q L∞. (1.20) Lemma 1.5. Let 0< γ <1 and 0< q≤ ∞. Let{εk}k∈Nbe a sequence of positive real num- bers such that {εk}k∈N|q =A <∞. Then the sequences δk=k
j=0γk−jεj and ηk= ∞
j=kγj−kεjbelong toq, and the estimate δk
k∈N|q+ ηk
k∈N|q≤cA (1.21)
holds. The constantcdepends only onγandq.
Lemma 1.6. Let 0< p≤ ∞andγ >0. Let{fj}j∈N⊂Lpbe a sequence of functions such that suppfj⊂ {ξ∈Rn:|ξ| ≤γ2j}. Then the estimate
Δkfj|Lp≤c2(j−k)ρfj|Lp
k≤j <∞,ρ=max
0,n p−n
(1.22) holds. The constantcdepends only onn,p, andγ.
Lemma 1.7. Let 0< p <1 andγ >0. Let{fj}j∈N⊂Lpbe a sequence of functions such that suppfj⊂ {ξ∈Rn:|ξ| ≤γ2j}. Then the estimate
∞ j=0
fj|Bρp,∞
≤c 2jρfj
j∈N|Lp
∞
ρ=n
p−n
(1.23)
holds. The constantcdepends only onn,p, andγ.
Lemma 1.8. Let 0< p≤q≤ ∞andγ >0. Then there exists a constantc=c(n,p,q)>0 such that for all f ∈Lpwith suppf⊂ {ξ∈Rn:|ξ≤γ}, one has
f |Lq≤cγn(1/ p−1/q)f |Lp. (1.24)
ForLemma 1.4, we can see [11, Sections 2.3 and 2.8] and [12, Section 2.7].Lemma 1.5 follows from Young’s inequality inq. The proof ofLemma 1.6is given in [4, Section 2.4, Theorem 1(iii)] andLemma 1.7in [7, Lemma 3]. For the proof ofLemma 1.8, we can see [14, Proposition 2.13], 1≤p≤q≤ ∞, it is the classical inequality of Bernstein.
2. Multiplication of mixed type
The following results give an extension of the sufficient hypotheses used in [5, Theo- rem 6.1].
Theorem 2.1. Let 0< p,p1,p2<∞, 0< q,q2≤ ∞,−∞< s <∞, andr >0 be such that
−r+ max
0, n p1
+ n p2−n
< s <min n
p1
,r
, 1
p = 1 p1+ 1
p2−r n, 1
q2≥ 1 p2−r
n, r < n p2
resp.,r= n p2
.
(2.1)
Then it holds
Fsp1,q·Brp2,q2 Fsp,q resp.,Fsp1,q·
Bn/ pp2,∞2∩L∞ Fsp1,q. (2.2) Corollary 2.2. Under the hypotheses ofTheorem 2.1. Ifr < n/ p2(resp.,r=n/ p2) then it holds
Fps1,q·Frp2,q2 Fp,qs resp.,Fps1,q·Fn/ pp2,q22 Fps1,qforp2≤1. (2.3) Furthermore, in particular, if 1< p1<∞andr > n/ p1+n/ p2−n, can be takens=0 in (2.3).
Proof. SinceFrp2,q2Brp2,t witht=(1/ p2−r/n)−1, we obtain the first embedding. How- ever, the second embedding follows fromFn/ pp2,q22Bn/ pp2,∞2∩L∞. Remark 2.3. InCorollary 2.2, whenr < n/ p2(resp.,r=n/ p2), we obtain [10, Theorems 4.4.3/2(21) and 4.4.4/2(16) (resp., Theorems 4.4.3/2(22) and 4.4.4/2(17))]. The particu- lar cases=0 presents a complement of [10, Theorem 4.4.4/4(i)].
To proveTheorem 2.1, we need the following lemma.
Lemma 2.4. Let 0< p <∞anda > n/ p. Then there exists a constantc >0 such that Q∗j,agj∈N|Lp
∞≤cg|Fp,20 , (2.4) for anyg∈F0p,2.
Proof. First, we define the maximal function ofQjg, of Hardy-Littelewood type, by the formula
MQjg(x)=sup
r>0
B(x,r)1
B(x,r)
Qjg(y)d y, (2.5)
whereB(x,r) is the ball centered atxof radiusrand|B(x,r)|denotes its measure. Next, lett >0 satisfyn/a < t < p. From [13, Theorem 1.3.1], we have
Q∗j,ag(x)≤Q∗j,n/tg(x)≤cMQjgt(x)1/t ∀x∈Rn
. (2.6)
Then we obtain
sup
j∈NQ∗j,ag|Lp≤c
sup
j∈NMQjgt 1/t
|Lp=csup
j∈NMQjgt|Lp/t
1/t
≤csup
j∈N
Qjgt|Lp/t
1/t
.
(2.7)
A proof of the last inequality may be found in [13, Theorem 2.2.2, page 89]. Now, it is easy to see that the last member of (2.7) is bounded by
sup
j∈N
Qjg|Lp
≤cg|F0p,2. (2.8)
Inequality (2.8) follows from the equality between the local Hardy spaceshpandF0p,2, (cf.
see [12, Section 2.2, page 37, and Theorem 2.5.8/1]).
Proof ofTheorem 2.1
Case 1 (r < n/ p2). (i) Estimate of{Πk,1(f,g)}k∈N. Since Πk,1(f,g)(x)=
Rn
Ᏺ−1ϕ(y)Qk+1g·Δkfx−2−kyd y
≤cQ∗k+1,a1g(x)Δ∗k,a2f(x) ∀x∈Rn ,
(2.9)
whereQk∗,a1andΔ∗k,a2are defined as inRemark 1.3, we obtain 2ksΠk,1(f,g)k∈N|q≤csup
j∈N
Q∗j,a1g 2ksΔ∗k,a2fk∈N|q, (2.10)
wherea1anda2are real numbers at our disposal. We set 1/b=1/ p2−r/n. The left-hand side of (2.10), inLp-norm, is bounded by
csup
j∈NQ∗j,a1g|Lb 2ksΔ∗k,a2fk∈N|Lp1q. (2.11) Choosea1> n/banda2> n/min(p1,q), then bothLemma 2.4and the embeddingBrp2,q2 Fb,20 yield that (2.11) is estimated as desired.
(ii) Estimate of{Πk,2(f,g)}k∈N. Letu∈Rsuch that max
0, 1
p1−r n
<1 u<min
1 p1, 1
p1− s n
. (2.12)
We set
1 v=
1 p2+1
u, σ=s−n p+n
v, β=s− n p1+n
u. (2.13)
We have
σpLγv
Lγpsq, Fsp1,q Bβu,p1. (2.14) For the first embedding of (2.14), we can see [4, Section 2.3, Theorem 3]. On the other hand, the H¨older inequality yields
2kσΠk,2(f,g)|Lv≤c2krΔkg|Lp2 2kβ
k+1
j=0
2−jβ·2jβΔjf |Lu
. (2.15)
We set 1/q2=1/ p−1/ p1. Applying, successively, the H¨older inequality again inp-norm andLemma 1.5, we obtain the boundcg|Brp2,q2f |Bβu,p1. So (2.14) andBrp2,q2Brp2,q2 give
2ksΠk,2(f,g)k∈N|Lp
q≤cg|Brp2,q2f |Fsp1,q. (2.16) (iii) Estimate of{Πk,3(f,g)k∈N. We first consider 1/ p1+ 1/ p2≤1. Letu∈Rsuch that
max
0, 1 p1−r
n, 1 p1−r+s
n
< 1 u< 1
p1
. (2.17)
We use the notationsv,σ, andβfrom (2.13).Lemma 1.6provides 2kσΠk,3(f,g)|Lv≤c2k(β+r)
∞ j=k
2−j(β+r)·2j(β+r)Δjg|Lp2Δjf |Lu. (2.18) A similar argument as above yields
2kσΠk,3(f,g)k∈N|p
Lv≤c 2j(β+r)Δjg|Lp2Δjf |Lu
j∈N|p. (2.19) We set 1/q2=1/ p−1/ p1. By the H¨older inequality inp-norm, the right-hand side of (2.19) is bounded bycg|Brp2,q2f |Bβu,p1. Then we conclude the desired estimate by (2.14).
We now study case 1/ p1+ 1/ p2>1. Letu∈Rsuch that max
0, 1− 1
p2, 1 p1−r
n
< 1 u< 1
p1
. (2.20)
We employ the notationsυandσfrom (2.13). ByLemma 1.6, we obtain 2kσΠk,3(f,g)|Lv≤c2kμ
∞ j=k
2−jμ·2j(r+ρ)Δjg|Lp2Δjf |Lu, (2.21) whereρ=s−n/ p1+n/uandμ=s+r−n/ p1−n/ p2+n >0, therefore,
2kσΠk,3(f,g)k∈N|p
Lv≤c 2j(r+ρ)Δjg|Lp2Δjf |Lu
j∈N|p. (2.22)
On the right-hand side of (2.22), we employ the H¨older inequality in p-norm (with 1/ p=1/ p1+ 1/q2),Fsp1,qBu,pρ 1, andBrp2,q2Brp2,q2successively. Sinceσ > sandv < p, we can finish the proof of this case by applying, in the left-hand side of (2.22), embeddings (2.14).
Case 2 (r=n/ p2). We only estimate{Πk,1(f,g)}k∈N. It is sufficient to see that
2ksΠk,1(f,g)≤cg|L∞2ksΔ∗k,af (2.23)
witha > n/min(p1,q) and to take theLp1(q)-norm.
Theorem 2.5. Let 0< p,p1<∞, 0< p2,q≤ ∞,−∞< s <∞, andr >0 be such that
−r+ max
0, n p1+ n
p2−n
< s < r. (2.24)
If either of the following assertions is satisfied:
(i) 1/ p=1/ p1+ 1/ p2,
(ii) max(1/ p1,s/n) + max(0, 1/ p2−r/n)<1/ p <1/ p1+ 1/ p2, then it holds
Fps1,q·Brp2,∞ Fsp,q. (2.25) Corollary 2.6. Let p, p1,q,r,sbe as inTheorem 2.5and 0< p2<∞. If (i) or (ii) of Theorem 2.5is satisfied, then the embeddingFsp1,q·Frp2,∞Fsp,qholds.
The proof ofCorollary 2.6is immediate becauseFrp2,∞Brp2,∞.
Remark 2.7. We note thatTheorem 2.5(i) whenp2= ∞is given in [4, Section 3.2, The- orem 1]. Also, we note thatCorollary 2.6is given in both [5, Theorem 6.1 withr=pin formula (6.6)] and [10, Theorems 4.4.3/1(7) and 4.4.4/1(7)].
Proof ofTheorem 2.5(i). NotingRemark 2.7, we only need to treat the part 0< p2<∞. (i) Estimate of{Πk,1(f,g)}k∈N. From (2.9) andLemma 2.4, we have
2ksΠk,1(f,g)k∈N|Lp
q≤cg|F0p2,2f |Fsp1,q. (2.26)
By embeddingsBrp2,∞B0p2,min(p2,2)F0p2,2, we obtain that the last term of (2.26) is bounded by the desired quantity.
(ii) Estimate of{Πk,2(f,g)}k∈N. The H¨older inequality provides Πk,2(f,g)|Lp≤c
2−kr
k+1
j=0
2−j(s−r)·2−jr
g|Brp2,∞f |Bsp1,∞. (2.27)
The hypothesiss < ryields
2ksΠk,2(f,g)k∈N|min(p,q)Lp≤cg|Brp2,∞f |Bsp1,∞. (2.28)
Using embeddings
smin(p,q)Lγp
Lγp
sq, Fsp1,q Bsp1,∞, (2.29) we obtain the desired result.
(iii) Estimate of{Πk,3(f,g)}k∈N. We setρ=s+r−max(0,n/ p−n). UsingLemma 1.6, we obtain
2ksΠk,3(f,g)|Lp≤c2−kr·2kρ ∞ j=k
2−jρ2jrΔjg|Lp22jsΔjf |Lp1
≤c2−krg|Brp2,∞f |Bsp1,∞.
(2.30) In this inequality, we take min(p,q)-norm and we conclude the desired estimate us- ing (2.29).
Proof ofTheorem 2.5(ii). (1) Estimate of {Πk,1(f,g)}k∈N. We set 1/u=1/ p−1/ p1. As in (2.26), we have the boundcg|Fu,20 f |Fps1,qwhich, by the embeddingsBrp2,∞ Bn/ pp2,u2−n/uFu,20 , is estimated as desired.
(2) Estimate of {Πk,2(f,g)}k∈N. In part, for technical reasons, we prove this in three separate cases:
Case 1 (s <0). ByLemma 1.6, the H¨older inequality, andLemma 1.8, we have
Πk,2(f,g)|Lp≤c2(n/ p1+n/ p2−n/ p−r−s)kg|Brp2,∞f |Bsp1,∞. (2.31)
Since n/ p1+n/ p2−n/ p−r <0, we obtain an inequality of type (2.28) and finish the proof of this case using (2.29).
Case 2 (0≤s < n/ p1). We set 1/b=1/ p2+ 1/ p1−s/n. We continue with the following subcases.
Subcase 2.1 (r≤n/ p2andp≤b(ors≤n/ p2< randp≤b)). As inCase 1, we have Πk,2(f,g)|Lp≤cγk2−krg|Brp2,∞f |Bsp1,∞, (2.32)
where
γk=
⎧⎨
⎩
k+ 2 ifp=b,
1−2n/b−(n/ p)−s−1 ifp < b. (2.33)
Now since{2k(s−r)γk}k∈N∈min(p,q), we conclude the desired conclusion using (2.28) and (2.29).
Subcase 2.2 (r≤n/ p2andp > b(ors≤n/ p2< randp > b)). Letu >0 satisfy max
0,1
p− 1 p2
<1 u< 1
p1−s
n. (2.34)
We employ the notationsv,σ, andβfrom (2.13). We have
Πk,2(f,g)|Lv≤cg|Brp2,∞f |Bu,β∞2−k(β+r). (2.35) Since{2−k(β+r−σ)}k∈N∈p, we can finish the proof of this case using (2.14).
Subcase 2.3 (n/ p2< s < r). We have only casep < bneeds to be verified. As in (2.32), we immediately obtain the result.
Case 3 (s≥n/ p1). We have the following subcases.
Subcase 3.1 (p < p2). We set 1/v=1/ p−1/ p2. Observe that 2ksΠk,2(f,g)|Lp≤c2krΔkg|Lp2
2k(s−r)
k+1
j=0
2j(n/ p1−n/v)Δjf |Lp1
≤cg|Brp2,∞f |Bn/ pp1,∞1 2k(s−r)
k+1
j=0
2−jn/v
.
(2.36)
Then, we calculatemin(p,q)-norm and conclude the desired estimate by the fact that
2k(s−r)
k+1
j=0
2−jn/v
k∈N
∈min(p,q). (2.37)
Subcase 3.2 (s > n/ p1andp≥p2). It suffices to apply both embeddingBsp1,∞Bn/ pp1,11and (2.29) to
Πk,2(f,g)|Lp≤cΔkg|LpQk+1f |L∞
≤c2k(n/ p2−r−n/ p)g|Brp2,∞f |Bn/ pp1,11.
(2.38) Subcase 3.3 (s=n/ p1and p≥p2). We chooseα >0 such thatε=α−n/ p+n/ p1+n/ p2− r <0, then it suffices to apply (2.29) to
2kn/ p1Πk,2(f,g)|Lp≤c2kεg|Brp2,∞f |Bn/ pp1,∞1−α. (2.39) (3) Estimate of{Πk,3(f,g)}k∈N. The proof of this case is obtained similarly to the proof ofTheorem 2.1just by replacing (2.17) and (2.20) with
max
0,1 p−
1 p2, 1
p1−r+s n
< 1 u< 1
p1, max
0, 1− 1
p2,1 p−
1 p2
< 1 u< 1
p1,
(2.40)
respectively.
3. Multiplication of typesF·BandB·B
The next theorem presents a continuation of [3], [5, Theorem 6.1] ,[6], and [7, Section 5].