7 Pages

duality

Course: MATH 6327, Fall 2008
School: Georgia Tech
Rating:
 
 
 
 
 

Word Count: 1540

Document Preview

on Notes Norms and Duality by Eric Carlen In the previous section we saw how a certain class of convex functions , the Orlicz functions, induced norms on ceretain subspaces V of the space of measurable functions on some measure space (, S, ). We saw that for each such , V is complete in its norm, and hence is a Bancah space. So far in our analysis though we did not use all of the properties required of an Orlicz...

Register Now

Unformatted Document Excerpt

Coursehero >> Georgia >> Georgia Tech >> MATH 6327

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
on Notes Norms and Duality by Eric Carlen In the previous section we saw how a certain class of convex functions , the Orlicz functions, induced norms on ceretain subspaces V of the space of measurable functions on some measure space (, S, ). We saw that for each such , V is complete in its norm, and hence is a Bancah space. So far in our analysis though we did not use all of the properties required of an Orlicz function . In particular, we have not made any use of the requirement that (1) = 1. Nor have we made full use of the requirement that lims (s)/s = : lims (s) = would have sufficed in our proofs so far. We now explain the reasons for these requirements. Let (t) = sup{ts - (s)} s0 denote the convex function conjuagte to . Then we know that for any s, t 0 s (s) = (s) + ( (s)) provided is differentiable at s. In particular, under our assumptions, 1 = (1) + (1) . Since for all t, taking t = 1 we see ( ) (1) = (( ) (1)) + (1) . Now s = (s) + (1) t( ) (t) = (( ) (t)) + (t) (1) has at most one solution if is strictly convex. Since s = 1 is a solution, it follows in this case that ( ) (1) = 1 . also, it follws from (1) and (0) = (0) = 0 that (0) = 0. Since we also have t (t) = (t) + (( ) (t)) , (2) for all t, taking t = 0 we have that ( ) (0) = 0. We conclude that is an Orlicz function whenever is a strictly convex Orlicz function. We now apply Young's inequality for the pair , in order to deduce a generalization of Hlder's inequality. To do this, let a and b be any positive numbers, and let o a,b (s) = b(as) . 1 Then (t) = sup{ts - b(as)} a,b s0 = sup b s0 t as - b(as) ab . = b Young's inequality then gives us t ab st b(as) + b t ab for all s and t. Also, we know that there is equality only if t = ab (as) . Then for any f and g, |f ||g|d b (|af |)d + b |g| ab d . Now, by definition, |f | f d = (1) and |g| g d = (1) . Therefore, if we choose a= This gives us 1 f g and b= f g , |f ||g|d f ((1) + (1)) = f g . There is equality if and only if |g(x)| = ab (a|f (x)|) = g for almost every x. This prove the following Theorem 1 (Generalized Hlder's Inequality) Let be any strictly convex Orlicz o function and its conjugate function. Then for all measurabel functions f and g, |f ||g|d f 2 |f (x)| f g . (3) There is equlaity in (3) if and only if |g(x)| = g for almost very x. Now let f V be given. Is there a function g in V with |f ||g|d = f |f (x)| f (4) g (5) or is there not? If there is, we have just seen that we must have In case (s) = sp /p, (s) = sp-1 . Therefore, for any f in Lp , |f (x)| f = |f (x)| f p p-1 and the function on the right is clearly a unit vector Lp where p = p/(p - 1). Indeed, |f (x)| f p p-1 p/(p-1) d = |f (x)|p d = 1 . f p p Hence, for any f Lp , there is a unit vector g in Lp so that eqaulity holds in (5). This has an important consequence. Define p-1 |f (x)| , (6) h(x) = sgn(f (x)) f p where for any complex number , sgn() = /|| if = 0 , 0 if = 0 p and denotes the complex conjugate. Then h f hd = = 1, and we have p 1 f p |f |p = f . Now since f gd |f ||g|d with equality only in case sgn(g(x)) = sgn)f (x)) for all x such that |g(x)||f (x)| = 0. Then from the contiitions for eqaulity in Hlder's inequality, we see that if g is a unit vector in o p L and f hd = f p , then g = h where h is given by (6). 3 This shows that for any f in Lp , 1 < p < , there is one and only one unit vector h in Lp , p = p/(p - 1), so that f p = f hd . (7) It is also easy to generalize this result to p = 1 with p = in that case. We will save the discussion of L1 and L for the end of the section; the results in these cases are realtively straightforward. For now we restrict our attention to the case 1 < p < . There is a related result, which combined with these observations, is very useful. It is a sort of converse to Hlder's inequality due to Landau. We first state and prove it for o the classical Lp spaces. Theorem (Landau's 2: Thoerem) Let f be a measurable function on a sigma finite measure space (, S, ), and suppose that for some p with 1 < p < , |f h|d < (8) for all unit vectors h in Lp where p = p/(p - 1). Then f Lp . Proof: Let An be an increasing sequence of sets of finite measure so that = n An . Let f be any measurable complex valued function, and define Bn = |{ x : |f (x) n } An . Then = n An . Therefore, if we define fn (x) = f (x)1Bn (x) , we have that limn |fn (x)| = |f (x)| for all x. Clearly fn p n(An )1/p and so fn Lp for all n. By the Monotone Convergence Theorem, |f |p d = lim n |fn |p d Now since each fn Lp , we have that fn hn d = fn p, where hn is a unit vector in Lp . (In fact, hn is given in terms of fn by (6)). By the definition of fn , f hn d = fn hn d = fn 4 p . Now if sup |f h|d : sup fn h p 1 <, (9) then n0 p < and so |f |p d < , which is what we want to show in case (8) holds. It therefore suffices to show that (8) implies (9). Therefore, suppose that (8) holds, but (9) does not. Then we can choose a sequence {gn } of unit vectors in Lp so that f gn 0 and f gn d 2n . Now define h= 2-n gn . j=1 Then by convexity the pth power, |h(x)|p sum 2-n |gn (x)|p , j=1 and integration yields |h(x)|p d sum 2-n = 1 . j=1 But f hd = 2-n f gn d j=1 = j=1 2-n 2n = . Since h p 1, this contradicts (8). Thus (8) implies (9), and the result is proved. To apply this result, we first extend the norm function to all measurable functions f on (, S, ) by defining f p = if f inLp . With this definition, we have the following result: Theorem 3: (Dual Characterization of Lp Norms, 1 < p < ) Let f be a measurable function on a sigma finite measure space (, S, ). Then there is a unit vector h in Lp , p = p/(p - 1) such that f p = f hd . 5 (10) If f p is finite, this unit vector h is unique, and is given in terms of f by (6). Proof: If f Lp , so that f p < , this follows from the remarks above the statement of Landau's Theorem. If f p = , so that f Lp , it follows from Landau's Theorem that / p there is a unit vector h in L so that f hd = . Here is a simple application of this: Take any two vectors f and g in Lp . Then there is a unit vector h so that f +g But by Hlder's inequality, o f hd f p p = (f + g)hd = f hd + ghd . h p = f p and likewise ghd g f +g p h p ...

Textbooks related to the document above:
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

Georgia Tech - MATH - 6327
Notes on Uniform Smoothness by Eric Carlen In this section we are converned with the differentiablity properties of norms. Let V be a normed space with norm . The derivative gives the &quot;best linear approximation&quot; to a function, and so we say that a f
Georgia Tech - MATH - 6327
Notes on Uniform Convexity by Eric Carlen The unit ball of any normed vector space is convex, though it need not be strictly convex. For example, consider a measure space (, S, ). Let A and B be two subsets of with A B and (A) &lt; (B) . Let C = B Ac
Georgia Tech - MATH - 6327
Notes on Separability in Banach spaces by Eric Carlen Let V be Rn with its usual Euclidean norm. Given a sequence {vm } in V , and a vector v in V , then, by definition, limm vm = v weakly in casemlim f (vm ) = f (v)for all linear functionals f
Georgia Tech - MATH - 6327
The Banach Space C0 (X) and its Dual Let X be any complete, separable metric space, such as Rn , or any closed subset of R . We suppose also that for each x X, there is an open set Ux containing x that has compact closure. This property of X is call
Georgia Tech - MATH - 6327
Problems Set 1 for Math 6327. Due Wednesday, August 29 There are three problems on this problem set. The first two involve background material, and if they give you trouble, you will want to review the basic topology, such as is covered in our introd
Georgia Tech - MATH - 6327
Solutions for Problem Set One 1. Prove that if f (x) is a continuous real valued function on [0, 1], then for all is a &gt; 0 so that for all x and y in [0, 1], |x - y| &lt; |f (x) - f (y)| &lt; . &gt; 0, thereSolution: There are a number of ways to do this
Georgia Tech - MATH - 6327
Problems Set 2 for Math 6327. Due Friday, September 14 Problems from Chapter One of the Text: 3,4,10,18,19,20. The 7th and final problem is this: Problem 7: Let (, S, ) be a measure space. Show that ifM Ng(x) =j=1bj 1Bj (x) =j=1M cj 1Cj (x)
Georgia Tech - MATH - 6327
Solutions for Homework Problems 2 1 (Problem 3, chapter 1, Lieb and Loss) This provides a very good example of how one uses the monotone class theorem to prove that all sets in a algebra have some property. For this problem, let B be the Borel algebr
Georgia Tech - MATH - 6327
Test One, Math 6327, Fall 2001 (1.) Let (, S, ) be a measure space. Suppose that=n=1Anwith each An in S, and where the union is not necessarily disjoint. Let f be a real valued function on , and suppose that for each n there is a measurable f
Georgia Tech - MATH - 6327
Test One, Math 6327, Fall 2001 (1.) Let (, S, ) be a measure space. Suppose that=n=1Anwith each An in S, and where the union is not necessarily disjoint. Let f be a real valued function on , and suppose that for each n there is a measurable f
Georgia Tech - MATH - 6327
Problems Set 3 for Math 6327. Due Monday, October 22 Problem 1: Prove formula (6), page 161, with Cc () replaced by Cc (). (Besides this difference, one key part of proof of this in the text is left as an exercise to the reader).1
Georgia Tech - MATH - 6327
Solution for Problems Set 3, Math 6327 Problem 1: Prove that for any compact set K in , (K) inf { T () : Cc () , 1K } . (The notation is that of Section 6.22 of the text.) SOLUTION: We can do this very briefly since we know that for all continuo
Georgia Tech - MATH - 6327
Problems Set 4 for Math 6327. Due Wednesday, October 31 Problem 1: Problem 7 in Chpater 2 of the text. Problem 2: Problem 8 in Chpater 2 of the text. Problem 3: Show that for all p with 1 p , if f L1 (Rn ) and g Lp (Rn )L (Rn ), then f g Lp (Rn
Georgia Tech - MATH - 6327
Problems Set 5 for Math 6327. Due Wednesday, November 14 1 (A Projection Lemma Problem) Let (X, S, ) be a finite measure space. Fix p with 1 &lt; p &lt; . Let K be the set of non-negative functions in Lp (X, S, ) that satisfy d = 1 (That is, the set of pr
Georgia Tech - MATH - 6327
Problems Set 6 for Math 6327. Due Wednesday, December 5 1 Let V be C([0, 1]) with the supremum norm as usual, and let B be the unit ball. Show that B is not strictly convex. 2 Define a function f |f | on C([0, 1]) by |f | - f1 +0|f (t)| dt2
Georgia Tech - MATH - 6327
Final Exam for Math 6327, Fall 2001 Problem 1: Let M(R) denote the space of all signed Borel measures on the real line equipped with the total variation norm. Given any two measures 1 and 2 in M(R), define a functional L1 ,2 on C0 (R) by L1 ,2 (f )
University of Florida - MMC - 5015
ERIC SMITHinvolvement1460 N.W. Third Place #315 Gainesville, FL 32603 e-mail: eman181@ufl.edumobile: 3 5 2 - 6 3 6 - 2 9 9 4Journalism and Communications College Council President Act as a liaison between student government and the college's s
Johns Hopkins - DATA - 6140
NutritionBatshaw, M. L. (1997). Children with Disabilities, 4th Edition. Baltimore: Paul H. Brookes Publishing Co. Development of Young Children with Disabilities #872.514 (61) Carol Ann HeathTypical Growth WeightNewborn gains 2030 grams
University of Florida - EML - 5595
J Neurophysiol 93: 609 613, 2005. First published September 1, 2004; doi:10.1152/jn.00681.2004.ReportA Limited Set of Muscle Synergies for Force Control During a Postural TaskLena H. Ting and Jane M. MacphersonNeurological Sciences Institute,
Georgia Tech - PHYSICS - 2501
Physics 2501Test form000Name _PRACTICE QUIZ 1TEST FORM = THREE DIGIT NUMBER AT THE TOP OF THIS TEST STUDENT NUMBER = YOUR FULL 9-DIGIT GEORGIA TECH ID NUMBER PRINT YOUR NAME, TEST FORM NUMBER, AND STUDENT NUMBER IN THE SECTION OF THE ANSWER
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Physics 2501Test form000Name _PRACTICE QUIZ 5TEST FORM = THREE DIGIT NUMBER AT THE TOP OF THIS TEST STUDENT NUMBER = YOUR FULL 9-DIGIT GEORGIA TECH ID NUMBER PRINT YOUR NAME, TEST FORM NUMBER, AND STUDENT NUMBER IN THE SECTION OF THE ANSWER
Georgia Tech - PHYSICS - 2501
Physics 2501Test form000Name _PRACTICE QUIZ 6TEST FORM = THREE DIGIT NUMBER AT THE TOP OF THIS TEST STUDENT NUMBER = YOUR FULL 9-DIGIT GEORGIA TECH ID NUMBER PRINT YOUR NAME, TEST FORM NUMBER, AND STUDENT NUMBER IN THE SECTION OF THE ANSWER
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Georgia Tech - PHYSICS - 2501
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0INTRODUCTIONTOTHE FUTURES RESEARCH METHODS SERIESbyJerome C. GlennIntroduction I. Why Futures Methodology? II. What is Futures Research and Studies? III. Futures Research for Policy v
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0INTRODUCTIONTO THE FUTURES RESEARCH METHODS SERIESbyJerome C. GlennIntroduction I. Why Futures Methodology? II. What is Futures Research and Studies? III. Futures Research for Policy vs
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methodology-ENVIRONMENTAL SCANNINGByTheodore J. Gordon and Jerome C. Glenn I. History and Introduction: Objectives of Environmental Scanning II. What is Environment Scanning III. How to do itSome Sca
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0ENVIRONMENTAL SCANNINGByTheodore J. Gordon and Jerome C. Glenn I. History and Introduction: Objectives of Environmental Scanning II. What is Environment Scanning III. How to do itSome Scan
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0TEXT MINING OF SCIENCE &amp; TECHNOLOGY INFORMATION RESOURCES FOR FUTURE-ORIENTED TECHNOLOGY ANALYSESby Alan L. PorterI. History of the Method II. Description of the Method III. How to Do It I
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0TEXT MINING OF SCIENCE &amp; TECHNOLOGY INFORMATION RESOURCES FOR FUTURE-ORIENTED TECHNOLOGY ANALYSESby Alan L. PorterI. History of the Method II. Description of the Method III. How to Do It I
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE DELPHI METHODbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Method VI. Sa
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE DELPHI METHODbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Method VI. Sa
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE REAL-TIME DELPHI METHODByTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses V. Frontiers of the Method VI. Sample
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE REAL-TIME DELPHI METHODByTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses V. Frontiers of the Method VI. Sample
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methodology-THE FUTURES WHEELby Jerome C. GlennI. History of the Method II. Description of the Method III. How to Do ItA. Basic Futures Wheel B. Distinguishing Between Consequences C. Creating Forec
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE FUTURES WHEELby Jerome C. GlennI. History of the Method II. Description of the Method III. How to Do ItA. Basic Futures Wheel B. Distinguishing Between Consequences C. Creating Foreca
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE FUTURES POLYGONbyAntonio PacinelliI. History of the Method II. What is the Method III. How to Do It IV. Strengths and Weaknesses V. Use in Combination with other Methods VI. Speculat
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE FUTURES POLYGONbyAntonio PacinelliI. History of the Method II. What is the Method III. How to Do It IV. Strengths and Weaknesses V. Use in Combination with other Methods VI. Speculat
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methodology-TREND IMPACT ANALYSISbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Method A
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0TREND IMPACT ANALYSISbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Method Ap
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methodology-CROSS-IMPACT ANALYSISbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Samples of Applications V
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0CROSS-IMPACT ANALYSISbyTheodore J. GordonI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Samples of Applications VI
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0WILD CARDSby John L. Petersen and Karlheinz Steinmller with assistance from Hanna AdeyemaI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weakness
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0WILD CARDSby John L. Petersen and Karlheinz Steinmller with assistance from Hanna AdeyemaI. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknes
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methods-STRUCTURAL ANALYSIS WITH THE MICMAC METHOD &amp; ACTORS' STRATEGY WITH MACTOR METHODby1Jacques Arcade, Sirius Michel Godet, CNAM Francis Meunier, CNAM Fabrice Roubelat, CNAM I. Introduction: the
Penn State - NC - 5014
The Millennium ProjectFutures Research Methods-V3.0STRUCTURAL ANALYSIS WITH THE MICMAC METHOD &amp; ACTORS' STRATEGY WITH MACTOR METHODby1Jacques Arcade, Sirius Michel Godet, CNAM Francis Meunier, CNAM Fabrice Roubelat, CNAM I. Introduction: the S
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methodology-THE SYSTEMS PERSPECTIVE: METHODS AND MODELS FOR THE FUTUREbyAllenna Leonard with Stafford BeerI. IntroductionA Brief History The Field Today Time and Motion Probability Complexity and
Penn State - NC - 5014
The Millennium ProjectFutures Research Methodology-V3.0THE SYSTEMS PERSPECTIVE: METHODS AND MODELS FOR THE FUTUREbyAllenna Leonard with Stafford BeerI. IntroductionA Brief History The Field TodayII. Focusing on the System as a Purposeful
Penn State - NC - 5014
The Millennium Project V3.0Futures Research Methods-DECISION MODELINGbyThe Futures Group International1I. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Me
Penn State - NC - 5014
The Millennium ProjectFutures Research Methods-V3.0DECISION MODELINGbyThe Futures Group International1I. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Frontiers of the Met