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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

f(ξ)= f(ξ)=

Rn f(x)eix·ξdx ξRn

(1.2)

Hindawi Publishing Corporation

International Journal of Mathematics and Mathematical Sciences Volume 2006, Article ID 76182, Pages1–18

DOI10.1155/IJMMS/2006/76182

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andᏲ1f denotes the inverse Fourier transform of f; as usualᏲandᏲ1are extended from᏿to᏿.

Consider a partition of unity ψ(ξ) +

j=1

ϕ2jξ=1 ξRn

, (1.3)

whereϕ,ψC are positive functions such that suppϕ⊂ {ξRn: 1≤ |ξ| ≤3} and suppψ⊂ {ξRn:|ξ| ≤3}. We define the convolution operatorsQj andΔkby the fol- lowing:

Qjf =1ψ2j·

f (j=1, 2,. . .), Δkf =1ϕ2k·

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∈NSsuch that suppfk {ξRn:|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

Δk,afx=sup

y∈Rn

Δkfxy

1 +2k|y|a (1.8)

for allxRn, f ,a >0, andk=0, 1,. . . .Then, inDefinition 1.2(i) (resp., (ii)), we can replace Δkf byΔk,af witha >(n/min(p,q)) (resp., a > n/ p), (cf. see [13, Theo- rem 2.3.2]).

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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,1k,2k,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=k2ΔjandΔk=k+1

j=k1Δj.

In the below proofs of the different cases of type (1.1), written as G1·G2G3, to see f ·gbelongs toG3, (f G1,gG2), 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

s0s1, s0 n

p0 =s1 n p1

q0q1for 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=sn/ p=s1n/ p1. If

s0> s > s1, q0pq1, (1.15) or

s0=s=s1, q0min(p,q), q1max(p,q), (1.16) then it holds

Bsp00,q0 Fsp,q Bsp11,q1. (1.17)

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(iii) Let−∞< s <, 0< p <(resp., 0< p≤ ∞), and 0< q≤ ∞. If s >n

p, (1.18)

or

s=n

p, 0< p1 (resp., 0< q1), (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=0γkjεj and ηk=

j=kγjkεjbelong toq, and the estimate δk

k∈N|q+ ηk

k∈N|qcA (1.21)

holds. The constantcdepends only onγandq.

Lemma 1.6. Let 0< p≤ ∞andγ >0. Let{fj}j∈NLpbe a sequence of functions such that suppfj⊂ {ξRn:|ξ| ≤γ2j}. Then the estimate

Δkfj|Lpc2(jk)ρfj|Lp

kj <,ρ=max

0,n pn

(1.22) holds. The constantcdepends only onn,p, andγ.

Lemma 1.7. Let 0< p <1 andγ >0. Let{fj}j∈NLpbe a sequence of functions such that suppfj⊂ {ξRn:|ξ| ≤γ2j}. Then the estimate

j=0

fj|Bρp,

c 2fj

j∈N|Lp

ρ=n

pn

(1.23)

holds. The constantcdepends only onn,p, andγ.

Lemma 1.8. Let 0< pq≤ ∞andγ >0. Then there exists a constantc=c(n,p,q)>0 such that for all f Lpwith suppf⊂ {ξRn:|ξγ}, one has

f |Lqn(1/ p1/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], 1pq≤ ∞, it is the classical inequality of Bernstein.

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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 p2n

< s <min n

p1

,r

, 1

p = 1 p1+ 1

p2r n, 1

q2 1 p2r

n, r < n p2

resp.,r= n p2

.

(2.1)

Then it holds

Fsp1,q·Brp2,q2 Fsp,q resp.,Fsp1,q·

Bn/ pp2,2L 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,qforp21. (2.3) Furthermore, in particular, if 1< p1<andr > n/ p1+n/ p2n, can be takens=0 in (2.3).

Proof. SinceFrp2,q2Brp2,t witht=(1/ p2r/n)1, we obtain the first embedding. How- ever, the second embedding follows fromFn/ pp2,q22Bn/ pp2,2L. 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 Qj,agj∈N|Lp

cg|Fp,20 , (2.4) for anygF0p,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

Qj,ag(x)Qj,n/tg(x)cMQjgt(x)1/t xRn

. (2.6)

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Then we obtain

sup

j∈NQj,ag|Lpc

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

1ϕ(y)Qk+1g·Δkfx2kyd y

cQk+1,a1g(x)Δk,a2f(x) xRn ,

(2.9)

whereQk,a1andΔk,a2are defined as inRemark 1.3, we obtain 2ksΠk,1(f,g)k∈N|qcsup

j∈N

Qj,a1g 2ksΔk,a2fk∈N|q, (2.10)

wherea1anda2are real numbers at our disposal. We set 1/b=1/ p2r/n. The left-hand side of (2.10), inLp-norm, is bounded by

csup

j∈NQj,a1g|Lb 2ksΔk,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. LetuRsuch that max

0, 1

p1r n

<1 u<min

1 p1, 1

p1 s n

. (2.12)

We set

1 v=

1 p2+1

u, σ=sn p+n

v, β=s n p1+n

u. (2.13)

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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

2Πk,2(f,g)|Lvc2krΔkg|Lp2 2

k+1

j=0

2·2Δjf |Lu

. (2.15)

We set 1/q2=1/ p1/ 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

qcg|Brp2,q2f |Fsp1,q. (2.16) (iii) Estimate of{Πk,3(f,g)k∈N. We first consider 1/ p1+ 1/ p21. LetuRsuch that

max

0, 1 p1r

n, 1 p1r+s

n

< 1 u< 1

p1

. (2.17)

We use the notationsv,σ, andβfrom (2.13).Lemma 1.6provides 2Πk,3(f,g)|Lvc2k(β+r)

j=k

2j(β+r)·2j(β+r)Δjg|Lp2Δjf |Lu. (2.18) A similar argument as above yields

2Πk,3(f,g)k∈N|p

Lvc 2j(β+r)Δjg|Lp2Δjf |Lu

j∈N|p. (2.19) We set 1/q2=1/ p1/ 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. LetuRsuch that max

0, 1 1

p2, 1 p1r

n

< 1 u< 1

p1

. (2.20)

We employ the notationsυandσfrom (2.13). ByLemma 1.6, we obtain 2Πk,3(f,g)|Lvc2

j=k

2·2j(r+ρ)Δjg|Lp2Δjf |Lu, (2.21) whereρ=sn/ p1+n/uandμ=s+rn/ p1n/ p2+n >0, therefore,

2Πk,3(f,g)k∈N|p

Lvc 2j(r+ρ)Δjg|Lp2Δjf |Lu

j∈N|p. (2.22)

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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|L2ksΔk,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

p2n

< 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/ p2r/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

qcg|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)|Lpc

2kr

k+1

j=0

2j(sr)·2jr

g|Brp2,f |Bsp1,. (2.27)

The hypothesiss < ryields

2ksΠk,2(f,g)k∈N|min(p,q)Lpcg|Brp2,f |Bsp1,. (2.28)

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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+rmax(0,n/ pn). UsingLemma 1.6, we obtain

2ksΠk,3(f,g)|Lpc2kr·2 j=k

22jrΔjg|Lp22jsΔjf |Lp1

c2krg|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/ p1/ p1. As in (2.26), we have the boundcg|Fu,20 f |Fps1,qwhich, by the embeddingsBrp2, Bn/ pp2,u2n/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)|Lpc2(n/ p1+n/ p2n/ prs)kg|Brp2,f |Bsp1,. (2.31)

Since n/ p1+n/ p2n/ pr <0, we obtain an inequality of type (2.28) and finish the proof of this case using (2.29).

Case 2 (0s < n/ p1). We set 1/b=1/ p2+ 1/ p1s/n. We continue with the following subcases.

Subcase 2.1 (rn/ p2andpb(orsn/ p2< randpb)). As inCase 1, we have Πk,2(f,g)|Lpk2krg|Brp2,f |Bsp1,, (2.32)

where

γk=

k+ 2 ifp=b,

12n/b(n/ p)s1 ifp < b. (2.33)

Now since{2k(sr)γk}k∈Nmin(p,q), we conclude the desired conclusion using (2.28) and (2.29).

Subcase 2.2 (rn/ p2andp > b(orsn/ p2< randp > b)). Letu >0 satisfy max

0,1

p 1 p2

<1 u< 1

p1s

n. (2.34)

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We employ the notationsv,σ, andβfrom (2.13). We have

Πk,2(f,g)|Lvcg|Brp2,f |Bu,β2k(β+r). (2.35) Since{2k(β+rσ)}k∈Np, 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 (sn/ p1). We have the following subcases.

Subcase 3.1 (p < p2). We set 1/v=1/ p1/ p2. Observe that 2ksΠk,2(f,g)|Lpc2krΔkg|Lp2

2k(sr)

k+1

j=0

2j(n/ p1n/v)Δjf |Lp1

cg|Brp2,f |Bn/ pp1,1 2k(sr)

k+1

j=0

2jn/v

.

(2.36)

Then, we calculatemin(p,q)-norm and conclude the desired estimate by the fact that

2k(sr)

k+1

j=0

2jn/v

k∈N

min(p,q). (2.37)

Subcase 3.2 (s > n/ p1andpp2). It suffices to apply both embeddingBsp1,Bn/ pp1,11and (2.29) to

Πk,2(f,g)|LpcΔkg|LpQk+1f |L

c2k(n/ p2rn/ p)g|Brp2,f |Bn/ pp1,11.

(2.38) Subcase 3.3 (s=n/ p1and pp2). We chooseα >0 such thatε=αn/ p+n/ p1+n/ p2 r <0, then it suffices to apply (2.29) to

2kn/ p1Πk,2(f,g)|Lpc2g|Brp2,f |Bn/ pp1,1α. (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

p1r+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].

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