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SERGEI CHOBANYAN, SHLOMO LEVENTAL, AND HABIB SALEHI Received 26 March 2005; Accepted 7 September 2005 The goal of the paper is twofold: 1 to show that the exact valueD2in the Me Rademach

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SERGEI CHOBANYAN, SHLOMO LEVENTAL, AND HABIB SALEHI

Received 26 March 2005; Accepted 7 September 2005

The goal of the paper is twofold: (1) to show that the exact valueD2in the Me Rademacher inequality equals 4/3, and (2) to give a new proof of the Me ´nshov-Rademacher inequality by use of a recurrence relation The latter gives the asymptotic estimate lim supn D n / log22n ≤1/4.

Copyright © 2006 Sergei Chobanyan et al This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

1 Introduction

The Me ´nshov-Rademacher inequality deals with the estimation of

D n =sup E max

1≤ k ≤ n

k

l =1

α l ϕ l

 2

where sup is taken over all probability spaces (Ω,Ᏺ,P), all real orthonormal systems (ϕ1, , ϕ n) on them, and all real coefficient collections (α1, , α n) withn

1α2

i =1 Rademacher [9] and Me ´nshov [7] independently proved that there exists an absolute constantC > 0 such that for each n ≥2,

A traditional proof using a bisection method (see, e.g., Doob [2] and Lo`eve [6]) leads to the inequality

D n ≤log2n + 2 2

Kounias [4] used a trisection method to get a finer inequality:

D n ≤

log

2n

log23+ 2

2

Hindawi Publishing Corporation

Journal of Inequalities and Applications

Volume 2006, Article ID 68969, Pages 1 7

DOI 10.1155/JIA/2006/68969

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The aim of this paper is twofold: to show that the exact starting valueD2=4/3 and to

establish a recurrence relation which leads to a refinement of (1.4) and an asymptotic constant1/4 Note that there are several other proofs of the Me ´nshov-Rademacher

in-equality and its generalizations, see, for example, Somogyi [10] and M ´oricz and Tandori [8]

Section 2 deals with the proof ofD2=4/3, whileSection 3 is devoted to the proof

of the Me ´nshov-Rademacher inequality with the asymptotic constant1/4.Section 4 contains alternative proofs to those results using the concept of main triangle projec-tion, a subject which was studied in depth in Gohberg and Kre˘ın [3] and Kwapie ´n and

“Pełczy ´nski” [5]

2 The value ofD2

Theorem 2.1 D2=4/3.

The proof of the theorem is based on the following lemma which may be of indepen-dent interest

Lemma 2.2 Let c > 0 , p c ≡ c2/(1 + c2), and define

f (p, c) = sup

X ∈ Ꮽ(p,c)E

where

Ꮽ(p,c) = {X ∈ L0(Ω,Ᏺ,P) : E(X)=0, E(X2)=1,P(X > −c) = p}. (2.2)

Then

Proof of Lemma 2.2 To show that the left-hand side is greater than or equal to right-hand

side, we observe that E(X p1X p > − c)= p(1 − p), where the distribution of X p ∈ Ꮽ(p,c) is

given by

p = P



X p =

(1− p) p



=1− P



X p = −

p

(1− p)



To see that the left-hand side is less than or equal to right-hand side, we define

h p(x) = x ·1x> − c − p · x −

p(1 − p)

The maximum ofh p(x) is achieved at x = (1− p)/ p and at − p/(1 − p) for the regions

x > −c and x ≤ −c, respectively We conclude that for any X ∈ Ꮽ(p,c),

0E

h p

X p

E

h p(X)

=E

X p ·1Xp > − c

E

X ·1X>− c

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Let us note also thatᏭ(p,c) is empty for p < p c Indeed, by the Chebyshev inequality,

E(X) =0 and E(X2)=1 implyP(X ≤ −c) ≤1/(1 + c2)=1− p c

Proof of Theorem 2.1 The result follows by standard calculations from the representation

a2 +b2=1,b2/(1+3a2 )<p<1

a2+b2p + 2ab · p(1 − p) (2.7)

To prove (2.7) convert an orthonormal pair (ϕ1,ϕ2) defined on (Ω,Ᏺ,P) into (X ≡ ϕ1/

ϕ2, 1) The new pair is orthonormal with respect to the measuredP  = ϕ2dP Also

EPmax

1  2 ,

1+2  2 

=EPmax

(aX)2, (aX + b)2 

= a2+b2P (X > −b/2a) + 2ab ·EP

X ·1X>− b/2a



≤ a2+b2p + 2ab · f



p, b

2a

 ,

(2.8)

wherep = P (X > − b/2a) Now (2.7) follows fromLemma 2.2withc = b/2a. 

3 An induction proof of the Me ´nshov-Rademacher inequality

Theorem 3.1 (i)

D m ≤1

4



3 + log2m 2

In particular, (ii)

lim sup

m

D m

log22m ≤1

Lemma 3.2 The following recurrence relation holds true for any n ∈ N:

Proof of Lemma 3.2 We have for any n ∈ N,

max

k ≤2n







k



1

α i ϕ i





2

max

 max

k ≤ n







k

 1

α i ϕ i





2 ,







n

 1

α i ϕ i



+ maxn<k ≤2n







k



n+1

α i ϕ i





 2 

max

k ≤ n







k

 1

α i ϕ i





2 + 2







n

 1

α i ϕ i



n<kmax2n







k



n+1

α i ϕ i



+ maxn<k ≤2n







k



n+1

α i ϕ i





2

.

(3.4) Taking expectations in (3.4) and using the Cauchy-Schwartz inequality, we come to the

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desired recurrence relation:

D2n ≤ pD n+ 2 p(1 − p)D n+ (1− p)D n = D n+ D n, (3.5) wherep =n

1α2i

Proof of Theorem 3.1 Lemma 3.2implies that for anyn ∈ N,

D12/2 n ≤ D1/2

SinceD1=1, this implies that for eachn ∈ N,

D12/2 n ≤1 +n

Let us take now 2n ≤ m < 2 n+1 Then

D m ≤ D2n+1 ≤



1 +n + 1 2

2



1 +log2m + 1 2

2

Remark 3.3 (1) The proof ofTheorem 3.1is a refinement of that appeared in Chobanyan [1]

(2) Kounias’s result mentioned in the introduction leads to lim sup(D n / log22n) ≤

(log 2/ log 3)2which is larger than 1/4 ofTheorem 3.1

4 An alternative approach: the main triangle projection

Consider the space L(Rn) of all linear operators (matrices) acting inRn The correspon-dence between the operators and matrices is given bya i j =(Ae j,e i), i, j =1, , n The main triangle projection T n: L(Rn)L(Rn) is a linear operator introduced as follows For

anA ∈L(Rn), the matrix of the operatorB = T n A has the form b i j = a i j ifi + j ≤ n + 1

andb i j =0 otherwise

We assume thatRnis endowed with the Euclidean norm, and the norm in L(Rn) is the usual operator norm

Theorem 4.1 D n = T n 2, n ∈ N.

Proof Let us prove first that T n 2sup A ≤1T n A2≤ D n Since the orthogonal

op-erators (and only them) are the extreme points of the unit ball of L(Rn), it suffices to show that for any orthogonal operatoru ∈L(Rn), T n u2≤ D n Let us relate with u the

orthonormal systemϕ1, , ϕ ndefined on (Ω,P), where Ω= {1, , n}, P( j) =1/n, j =

1, , n, as follows:

ϕ k(j) = √ n

ue k,e j , k, j =1, , n. (4.1)

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We have for any vectorα =(α1, , α n)∈ R nwith|α| =1,

D n ≥E max

k ≤ n







k



i =1

α i ϕ i





2

=

n



j =1

max

k ≤ n







k



i =1

α i

ue i,e j 



 2

n



j =1







n −j+1

i =1

α i

ue i,e j 





2

=T n u

α 2

.

(4.2)

Taking supremum over all orthogonalu’s and α’s from the unit ball ofRn, we getD n ≥

T n 2 To prove the inverse inequality, consider an orthonormal system (ϕ1, , ϕ n)

L2(Ω,Ᏺ,P) and any vector α =(α1, , α n)∈ R nwith|α| =1

I(α, ϕ) ≡E max

k ≤ n







k



i =1

α i ϕ i





2

=

n



k =1

E1S k





k



i =1

α i ϕ i





2

where S k = {ω ∈ Ω : the minimum of l s at which|l

i =1α i ϕ i(ω)|attains its maximum equalsk} Then we have

I(α, ϕ) =sup

g

n



k =1



Eg k1S k





k



i =1

α i ϕ i







 2

where supremum is taken over all collectionsg =( 1, , g n) such thatg k’s vanish outside

ofS kandg k 2=1,k =1, , n We have further

I(α, ϕ) =sup

g

n



k =1

k



i, j =1

α i α jE g k ϕ i ϕ j

=sup

g

n



i, j =1

n



k =max(i, j)

α i α jE g k ϕ i ϕ j =sup

g

T n Aα 2

,

(4.5)

where (Ae j,e i)=Eg n − j+1 · ϕ i,i, j =1, , n We have

A =sup

| α |=1

n



i =1

n

j =1

Eα j g n − j+1 ϕ i

 2

=sup

| α |=1

n



i =1



Ef ϕ i 2

=sup

| α |=1

Ef2=1, (4.6)

where f = α j g j, ifω ∈ S j, j =1, , n Therefore, (4.5) impliesD n ≤ T n 2 The theorem

The following corollary is ourTheorem 2.1

Corollary 4.2 D2=4/3.

Proof We have according toTheorem 4.1,

D2=T2 2

=sup

u

T2u 2

=sup







a b

b 0







2 :a2+b2=1



=4



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Remark 4.3 It follows from the proof ofTheorem 4.1thatD n =sup E[maxj(j

l =1a l ϕ l)2], where the supremum is over all real orthonormal systemsϕ1, , ϕ n, where eachϕ j, j =

1, , n takes at most n values, and all reals α1, , α nwith|α| =1

The following lemma establishes a finer recurrence relation thanLemma 3.2 However, the two lemmas are asymptotically equivalent

Lemma 4.4

D2n ≤4

3D n if D n ≤3, D2n ≤ D n −1

2+

D n −3

4 if D n ≥3. (4.8)

Proof We have for any n ∈ N:

T2n  =sup







A T n B

T n C 0









where the supremum runs over all matricesA, B, C, and D in L(Rn) such that(A B C D) ≤

1 For such matrices A, B, C, and D we check that |uA|2+|uT n B|2≤ T n 2|u|2 and

|Ax|2+|T n Cx|2≤ T n 2|x|2for allu, x ∈ R n Therefore,T2n  ≤sup{(u, Ax) + (u, F y) +

(v, Gy) : u, v, x, y ∈ R n,|u|2+|v|21,|x|2+|y|21,A, F, G ∈L(Rn),A ≤1,|wA|2+

|wF|2≤ D n |w|2,|Az|2+|Gz|2≤ D n |z|2for allw, z ∈ R n

The last supremum can easily

be computed and its square equals supa ∈[0,1](D n − a/2 +

D n a−3a2/4) Hence, D2n ≤

4/3D nifD n ≤3 andD2n ≤ D n −1/2 +

D n −3/4 if D n ≥3 This completes the proof of

Finally, it is known that for the Hilbert matrix (H n(i, j)=1/(i− j), if i = j and H n(i, i)=

0,i, j =1, , n, n ≥2),

T n H n

This along withTheorem 3.1implies the following bilateral estimate:

1

π2log22e ≤lim inf D n

log22n ≤lim sup D n

log22n ≤1

Acknowledgments

This work was supported in part by the US Civilian Research and Development Foun-dation Award GEMI-3328-TB-03 We want to express our gratitude to the anonymous referee for bringing to our attention the relationship betweenD n and the norm of the main triangle projection Furthemore, the results/proofs inSection 4are based on ideas, suggestions, and comments made by the referee

References

[1] S Chobanyan, Some remarks on the Men’shov-Rademacher functional, Matematicheskie Zametki

59 (1996), no 5, 787–790, translation in Mathematical Notes 59 (1996), no 5-6, 571–574.

[2] J L Doob, Stochastic Processes, John Wiley & Sons, New York, 1953.

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[3] I C Gohberg and M G Kre˘ın, Theory and Applications of Volterra Operators in Hilbert Space,

Izdat “Nauka”, Moscow, 1967, translated in Translations of Mathematical Monographs, vol 24, American Mathematical Society, Province, RI, 1970.

[4] E G Kounias, A note on Rademacher’s inequality, Acta Mathematica Academiae Scientiarum

Hungaricae 21 (1970), no 3-4, 447–448.

[5] S Kwapie ´n and A Pełczy ´nski, The main triangle projection in matrix spaces and its applications,

Studia Mathematica 34 (1970), 43–68.

[6] M Lo`eve, Probability Theory, 2nd ed., The University Series in Higher Mathematics, D Van

Nostrand, New Jersey, 1960.

[7] D Me ´nshov, Sur les s´eries de fonctions orthogonales, I, Fundamenta Mathematicae 4 (1923), 82–

105.

[8] F M ´oricz and K Tandori, An improved Menshov-Rademacher theorem, Proceedings of the

Amer-ican Mathematical Society 124 (1996), no 3, 877–885.

[9] H Rademacher, Einige S¨atze ¨uber Reihen von allgemeinen Orthogonalfunktionen, Mathematische

Annalen 87 (1922), no 1-2, 112–138.

[10] ´A Somogyi, Maximal inequalities for not necessarily orthogonal random variables and some

ap-plications, Analysis Mathematica 3 (1977), no 2, 131–139.

Sergei Chobanyan: Muskhelishvili Institute of Computational Mathematics, Georgian Academy of Sciences, 8 Akuri Street, Tbilisi 0193, Georgia

E-mail address:chobanya@stt.msu.edu

Shlomo Levental: Department of Statistics & Probability, Michigan State University, East Lansing,

MI 48824, USA

E-mail address:levental@stt.msu.edu

Habib Salehi: Department of Statistics & Probability, Michigan State University, East Lansing,

MI 48824, USA

E-mail address:salehi@stt.msu.edu

... betweenD n and the norm of the main triangle projection Furthemore, the results/proofs inSection 4are based on ideas, suggestions, and comments made by the referee

References... supported in part by the US Civilian Research and Development Foun-dation Award GEMI-3328-TB-03 We want to express our gratitude to the anonymous referee for bringing to our attention the relationship... n Since the orthogonal

op-erators (and only them) are the extreme points of the unit ball of L(Rn), it suffices to show that for any orthogonal

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