0 <β 1 let u(x) u(y) kuk u := sup u(x) and [u] β := sup
|
|
|
- Leon Powell
- 9 years ago
- Views:
Transcription
1 456 BRUCE K. DRIVER 24. Hölder Spaces Notation Let Ω be an open subset of R d,bc(ω) and BC( Ω) be the bounded continuous functions on Ω and Ω respectively. By identifying f BC( Ω) with f Ω BC(Ω), we will consider BC( Ω) as a subset of BC(Ω). For u BC(Ω) and 0 <β 1 let u(x) u(y) kuk u := sup u(x) and [u] β := sup x Ω x,y Ω x y β. x6=y If [u] β <, then u is Hölder continuous with holder exponent 43 β. The collection of β Hölder continuous function on Ω will be denoted by C 0,β (Ω) :={u BC(Ω) :[u] β < } and for u C 0,β (Ω) let (24.1) kuk C 0,β (Ω) := kuk u +[u] β. Remark If u : Ω C and [u] β < for some β>1, then u is constant on each connected component of Ω. Indeed, if x Ω and h R d then u(x + th) u(x) t [u] βt β /t 0 as t 0 which shows h u(x) =0for all x Ω. If y Ω is in the same connected component as x, then by Exercise 17.5 there exists a smooth curve σ :[0, 1] Ω such that σ(0) = x and σ(1) = y. So by the fundamental theorem of calculus and the chain rule, Z 1 Z d 1 u(y) u(x) = 0 dt u(σ(t))dt = 0 dt =0. 0 This is why we do not talk about Hölder spaces with Hölder exponents larger than 1. Lemma Suppose u C 1 (Ω) BC(Ω) and i u BC(Ω) for i =1, 2,...,d, then u C 0,1 (Ω), i.e. [u] 1 <. The proof of this lemma is left to the reader as Exercise Theorem Let Ω be an open subset of R d. Then (1) Under the identification of u BC Ω with u Ω BC (Ω),BC( Ω) is a closed subspace of BC(Ω). (2) Every element u C 0,β (Ω) has a unique extension to a continuous function (still denoted by u) on Ω. Therefore we may identify C 0,β (Ω) with C 0,β ( Ω) BC( Ω). (In particular we may consider C 0,β (Ω) and C 0,β ( Ω) to bethesamewhenβ>0.) (3) The function u C 0,β (Ω) kuk C 0,β (Ω) [0, ) is a norm on C 0,β (Ω) which make C 0,β (Ω) into a Banach space. Proof. 1. The first item is trivial since for u BC( Ω), the sup-norm of u on Ω agrees with the sup-norm on Ω and BC( Ω) is complete in this norm. 43 If β =1,uis is said to be Lipschitz continuous.
2 ANALYSIS TOOLS WITH APPLICATIONS Suppose that [u] β < and x 0 Ω. Let {x n } Ω be a sequence such that x 0 = lim x n. Then u(x n ) u(x m ) [u] β x n x m β 0 as m, n showing {u(x n )} is Cauchy so that ū(x 0) := lim u(x n ) exists. If {y n } Ω is another sequence converging to x 0, then u(x n ) u(y n ) [u] β x n y n β 0 as n, showing ū(x 0 ) is well defined. In this way we define ū(x) for all x Ω and let ū(x) =u(x) for x Ω. Since a similar limiting argument shows ū(x) ū(y) [u] β x y β for all x, y Ω it follows that ū is still continuous and [ū] β =[u] β. In the sequel we will abuse notation and simply denote ū by u. 3. For u, v C 0,β (Ω), v(y)+u(y) v(x) u(x) [v + u] β = sup x,y Ω x y β x6=y v(y) v(x) + u(y) u(x) sup x,y Ω x y β [v] β +[u] β x6=y and for λ C it is easily seen that [λu] β = λ [u] β. This shows [ ] β is a semi-norm on C 0,β (Ω) and therefore k k C 0,β (Ω) defined in Eq. (24.1) is a norm. To see that C 0,β (Ω) is complete, let {u n } be a C0,β (Ω) Cauchy sequence. Since BC( Ω) is complete, there exists u BC( Ω) such that ku u n k u 0 as n. For x, y Ω with x 6= y, u(x) u(y) u n (x) u n (y) x y β = lim x y β lim sup[u n ] β lim ku nk C 0,β (Ω) <, and so we see that u C 0,β (Ω). Similarly, u(x) u n (x) (u(y) u n (y)) (u m u n )(x) (u m u n )(y) x y β = lim m x y β lim sup[u m u n ] β 0 as n, m showing [u u n ] β 0 as n and therefore lim ku u n k C 0,β (Ω) =0. Notation Since Ω and Ω are locally compact Hausdorff spaces, we may define C 0 (Ω) and C 0 ( Ω) as in Definition We will also let C 0,β 0 (Ω) :=C 0,β (Ω) C 0 (Ω) and C 0,β 0 ( Ω) :=C 0,β (Ω) C 0 ( Ω). It has already been shown in Proposition that C 0 (Ω) and C 0 ( Ω) are closed subspaces of BC(Ω) and BC( Ω) respectively. The next proposition describes the relation between C 0 (Ω) and C 0 ( Ω). Proposition Each u C 0 (Ω) has a unique extension to a continuous function on Ω given by ū = u on Ω and ū =0on Ω and the extension ū is in C 0 ( Ω). Conversely if u C 0 ( Ω) and u Ω =0, then u Ω C 0 (Ω). In this way we may identify C 0 (Ω) with those u C 0 ( Ω) such that u Ω =0.
3 458 BRUCE K. DRIVER Proof. Any extension u C 0 (Ω) to an element ū C( Ω) is necessarily unique, since Ω is dense inside Ω. So define ū = u on Ω and ū =0on Ω. We must show ū is continuous on Ω and ū C 0 ( Ω). For the continuity assertion it is enough to show ū is continuous at all points in Ω. For any > 0, by assumption, the set K := {x Ω : u(x) } is a compact subset of Ω. Since Ω = Ω \ Ω, Ω K = and therefore the distance, δ := d(k, Ω), between K and Ω is positive. So if x Ω and y Ω and y x <δ,then ū(x) ū(y) = u(y) < which shows ū : Ω C is continuous. This also shows { ū } = { u } = K is compact in Ω and hence also in Ω. Since >0 was arbitrary, this shows ū C 0 ( Ω). Conversely if uª C 0 ( Ω) such that u Ω = 0 and > 0, then K := x Ω : u(x) is a compact subset of Ω which is contained in Ω since Ω K =. Therefore K is a compact subset of Ω showing u Ω C 0 ( Ω). Definition Let Ω be an open subset of R d,k N {0} and β (0, 1]. Let BC k (Ω) (BC k ( Ω)) denote the set of k times continuously differentiable functions u on Ω such that α u BC(Ω) ( α u BC( Ω)) 44 for all α k. Similarly, let BC k,β (Ω) denote those u BC k (Ω) such that [ α u] β < for all α = k. For u BC k (Ω) let kuk C k (Ω) = X k α uk u and α k kuk C k,β (Ω) = X k α uk u + X [ α u] β. α k α =k Theorem The spaces BC k (Ω) and BC k,β (Ω) equipped with k k C k (Ω) and k k C k,β (Ω) respectively are Banach spaces and BCk ( Ω) isaclosedsubspaceof BC k (Ω) and BC k,β (Ω) BC k ( Ω). Also C k,β 0 (Ω) =C k,β 0 ( Ω) ={u BC k,β (Ω) : α u C 0 (Ω) α k} is a closed subspace of BC k,β (Ω). Proof. Suppose that {u n } BCk (Ω) is a Cauchy sequence, then { α u n } is a Cauchy sequence in BC(Ω) for α k. Since BC(Ω) is complete, there exists g α BC(Ω) such that lim k α u n g α k u =0for all α k. Letting u := g 0, we must show u C k (Ω) and α u = g α for all α k. This will be done by induction on α. If α = 0 there is nothing to prove. Suppose that we have verified u C l (Ω) and α u = g α for all α l for some l<k.then for x Ω, i {1, 2,...,d} and t R sufficiently small, a u n (x + te i )= a u n (x)+ Letting n in this equation gives a u(x + te i )= a u(x)+ Z t 0 Z t 0 i a u n (x + τe i )dτ. g α+ei (x + τe i )dτ from which it follows that i α u(x) exists for all x Ω and i α u = g α+ei. This completes the induction argument and also the proof that BC k (Ω) is complete. 44 To say α u BC( Ω) means that α u BC(Ω) and α u extends to a continuous function on Ω.
4 ANALYSIS TOOLS WITH APPLICATIONS 459 It is easy to check that BC k ( Ω) is a closed subspace of BC k (Ω) and by using Exercise 24.1 and Theorem 24.4 that that BC k,β (Ω) is a subspace of BC k ( Ω). The fact that C k,β 0 (Ω) is a closed subspace of BC k,β (Ω) is a consequence of Proposition To prove BC k,β (Ω) is complete, let {u n } BCk,β (Ω) be a k k C k,β (Ω) Cauchy sequence. By the completeness of BC k (Ω) just proved, there exists u BC k (Ω) such that lim ku u n k C k (Ω) =0. An application of Theorem 24.4 then shows lim k α u n α uk C 0,β (Ω) =0for α = k and therefore lim ku u n k C k,β (Ω) =0. The reader is asked to supply the proof of the following lemma. Lemma The following inclusions hold. For any β [0, 1] BC k+1,0 (Ω) BC k,1 (Ω) BC k,β (Ω) BC k+1,0 ( Ω) BC k,1 ( Ω) BC k,β (Ω). Definition Let A : X Y be a bounded operator between two (separable) Banach spaces. Then A is compact if A [B X (0, 1)] is precompact in Y or equivalently for any {x n } X such that kx n k 1 for all n the sequence y n := Ax n Y has a convergent subsequence. Example Let X = 2 = Y and λ n C such that lim λ n =0, then A : X Y defined by (Ax)(n) =λ n x(n) is compact. Proof. Suppose {x j } j=1 2 such that kx j k 2 = P x j (n) 2 1 for all j. By Cantor s Diagonalization argument, there exists {j k } {j} such that, for each n, x k (n) =x jk (n) converges to some x(n) C as k. Since for any M <, x(n) 2 = lim x k (n) 2 1 k P we may conclude that x(n) 2 1, i.e. x 2. Let y k := A x k and y := A x. We will finish the verification of this example by showing y k y in 2 as k. Indeed if λ M =max λ n, then n M X ka x k A xk 2 = λ n 2 x k (n) x(n) 2 = X λ n 2 x k (n) x(n) 2 + λ M 2 x k (n) x(n) 2 M+1 λ n 2 x k (n) x(n) 2 + λ M 2 k x k xk 2 λ n 2 x k (n) x(n) 2 +4 λ M 2. Passing to the limit in this inequality then implies lim sup ka x k A xk 2 4 λ M 2 0 as M. k
5 460 BRUCE K. DRIVER Lemma If X A Y B Z are continuous operators such the either A or B is compact then the composition BA : X Z is also compact. Proof. If A is compact and B is bounded, then BA(B X (0, 1)) B(AB X (0, 1)) which is compact since the image of compact sets under continuous maps are compact. Hence we conclude that BA(B X (0, 1)) is compact, being the closed subset of the compact set B(AB X (0, 1)). If A is continuos and B is compact, then A(B X (0, 1)) is a bounded set and so by the compactness of B, BA(B X (0, 1)) is a precompact subset of Z, i.e. BA is compact. Proposition Let Ω o R d such that Ω is compact and 0 α<β 1. Then the inclusion map i : C β (Ω) C α (Ω) is compact. Let {u n } C β (Ω) such that ku n k C β 1, i.e. ku n k 1 and u n (x) u n (y) x y β for all x, y Ω. By Arzela-Ascoli, there exists a subsequence of {ũ n } of {u n } and u C o ( Ω) such that ũ n u in C 0. Since u(x) u(y) = lim ũ n(x) ũ n (y) x y β, u C β as well. Define g n := u ũ n C β, then [g n ] β + kg n k C 0 = kg n k C β 2 and g n 0 in C 0. To finish the proof we must show that g n 0 in C α. Given δ>0, g n (x) g n (y) [g n ] α =sup x6=y x y α A n + B n where gn (x) g n (y) A n =sup x y α : x 6= y and x y δ gn (x) g n (y) =sup x y β x y β α : x 6= y and x y δ δ β α [g n ] β 2δ β α and gn (x) g n (y) B n =sup x y α : x y >δ 2δ α kg n k C 0 0 as n. Therefore, lim sup [g n ] α lim sup A n + lim sup B n 2δ β α +0 0 as δ 0. This proposition generalizes to the following theorem which the reader is asked to proveinexercise24.2below. Theorem Let Ω be a precompact open subset of R d,α,β [0, 1] and k, j N 0. If j + β>k+ α, then C j,β Ω is compactly contained in C k,α Ω.
6 ANALYSIS TOOLS WITH APPLICATIONS Exercises. Exercise Prove Lemma Exercise Prove Theorem Hint: First prove C j,β C j,α Ω is compact if 0 α<β 1. Then use Lemma repeatedly to handle all of the other cases.
Metric Spaces. Chapter 7. 7.1. Metrics
Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some
n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n + 1 +...
6 Series We call a normed space (X, ) a Banach space provided that every Cauchy sequence (x n ) in X converges. For example, R with the norm = is an example of Banach space. Now let (x n ) be a sequence
1 Norms and Vector Spaces
008.10.07.01 1 Norms and Vector Spaces Suppose we have a complex vector space V. A norm is a function f : V R which satisfies (i) f(x) 0 for all x V (ii) f(x + y) f(x) + f(y) for all x,y V (iii) f(λx)
FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES
FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES CHRISTOPHER HEIL 1. Cosets and the Quotient Space Any vector space is an abelian group under the operation of vector addition. So, if you are have studied
BANACH AND HILBERT SPACE REVIEW
BANACH AND HILBET SPACE EVIEW CHISTOPHE HEIL These notes will briefly review some basic concepts related to the theory of Banach and Hilbert spaces. We are not trying to give a complete development, but
Notes on metric spaces
Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.
MATH 425, PRACTICE FINAL EXAM SOLUTIONS.
MATH 45, PRACTICE FINAL EXAM SOLUTIONS. Exercise. a Is the operator L defined on smooth functions of x, y by L u := u xx + cosu linear? b Does the answer change if we replace the operator L by the operator
SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties
SOLUTIONS TO EXERCISES FOR MATHEMATICS 205A Part 3 Fall 2008 III. Spaces with special properties III.1 : Compact spaces I Problems from Munkres, 26, pp. 170 172 3. Show that a finite union of compact subspaces
Metric Spaces Joseph Muscat 2003 (Last revised May 2009)
1 Distance J Muscat 1 Metric Spaces Joseph Muscat 2003 (Last revised May 2009) (A revised and expanded version of these notes are now published by Springer.) 1 Distance A metric space can be thought of
CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.
CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e. This chapter contains the beginnings of the most important, and probably the most subtle, notion in mathematical analysis, i.e.,
Lecture 1: Schur s Unitary Triangularization Theorem
Lecture 1: Schur s Unitary Triangularization Theorem This lecture introduces the notion of unitary equivalence and presents Schur s theorem and some of its consequences It roughly corresponds to Sections
Metric Spaces. Chapter 1
Chapter 1 Metric Spaces Many of the arguments you have seen in several variable calculus are almost identical to the corresponding arguments in one variable calculus, especially arguments concerning convergence
MATH PROBLEMS, WITH SOLUTIONS
MATH PROBLEMS, WITH SOLUTIONS OVIDIU MUNTEANU These are free online notes that I wrote to assist students that wish to test their math skills with some problems that go beyond the usual curriculum. These
Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics
Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights
Fixed Point Theorems
Fixed Point Theorems Definition: Let X be a set and let T : X X be a function that maps X into itself. (Such a function is often called an operator, a transformation, or a transform on X, and the notation
Metric Spaces. Lecture Notes and Exercises, Fall 2015. M.van den Berg
Metric Spaces Lecture Notes and Exercises, Fall 2015 M.van den Berg School of Mathematics University of Bristol BS8 1TW Bristol, UK [email protected] 1 Definition of a metric space. Let X be a set,
1. Prove that the empty set is a subset of every set.
1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: [email protected] Proof: For any element x of the empty set, x is also an element of every set since
MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform
MATH 433/533, Fourier Analysis Section 11, The Discrete Fourier Transform Now, instead of considering functions defined on a continuous domain, like the interval [, 1) or the whole real line R, we wish
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES
MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete
No: 10 04. Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics
No: 10 04 Bilkent University Monotonic Extension Farhad Husseinov Discussion Papers Department of Economics The Discussion Papers of the Department of Economics are intended to make the initial results
Lecture Notes on Measure Theory and Functional Analysis
Lecture Notes on Measure Theory and Functional Analysis P. Cannarsa & T. D Aprile Dipartimento di Matematica Università di Roma Tor Vergata [email protected] [email protected] aa 2006/07 Contents
THE BANACH CONTRACTION PRINCIPLE. Contents
THE BANACH CONTRACTION PRINCIPLE ALEX PONIECKI Abstract. This paper will study contractions of metric spaces. To do this, we will mainly use tools from topology. We will give some examples of contractions,
Mathematical Induction. Mary Barnes Sue Gordon
Mathematics Learning Centre Mathematical Induction Mary Barnes Sue Gordon c 1987 University of Sydney Contents 1 Mathematical Induction 1 1.1 Why do we need proof by induction?.... 1 1. What is proof by
FUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 2. OPERATORS ON HILBERT SPACES
FUNCTIONAL ANALYSIS LECTURE NOTES CHAPTER 2. OPERATORS ON HILBERT SPACES CHRISTOPHER HEIL 1. Elementary Properties and Examples First recall the basic definitions regarding operators. Definition 1.1 (Continuous
I. GROUPS: BASIC DEFINITIONS AND EXAMPLES
I GROUPS: BASIC DEFINITIONS AND EXAMPLES Definition 1: An operation on a set G is a function : G G G Definition 2: A group is a set G which is equipped with an operation and a special element e G, called
EXISTENCE AND NON-EXISTENCE RESULTS FOR A NONLINEAR HEAT EQUATION
Sixth Mississippi State Conference on Differential Equations and Computational Simulations, Electronic Journal of Differential Equations, Conference 5 (7), pp. 5 65. ISSN: 7-669. UL: http://ejde.math.txstate.edu
and s n (x) f(x) for all x and s.t. s n is measurable if f is. REAL ANALYSIS Measures. A (positive) measure on a measurable space
RAL ANALYSIS A survey of MA 641-643, UAB 1999-2000 M. Griesemer Throughout these notes m denotes Lebesgue measure. 1. Abstract Integration σ-algebras. A σ-algebra in X is a non-empty collection of subsets
HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!
Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following
Scalar Valued Functions of Several Variables; the Gradient Vector
Scalar Valued Functions of Several Variables; the Gradient Vector Scalar Valued Functions vector valued function of n variables: Let us consider a scalar (i.e., numerical, rather than y = φ(x = φ(x 1,
1. Let P be the space of all polynomials (of one real variable and with real coefficients) with the norm
Uppsala Universitet Matematiska Institutionen Andreas Strömbergsson Prov i matematik Funktionalanalys Kurs: F3B, F4Sy, NVP 005-06-15 Skrivtid: 9 14 Tillåtna hjälpmedel: Manuella skrivdon, Kreyszigs bok
Fuzzy Differential Systems and the New Concept of Stability
Nonlinear Dynamics and Systems Theory, 1(2) (2001) 111 119 Fuzzy Differential Systems and the New Concept of Stability V. Lakshmikantham 1 and S. Leela 2 1 Department of Mathematical Sciences, Florida
Introduction to Topology
Introduction to Topology Tomoo Matsumura November 30, 2010 Contents 1 Topological spaces 3 1.1 Basis of a Topology......................................... 3 1.2 Comparing Topologies.......................................
INCIDENCE-BETWEENNESS GEOMETRY
INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full
NOTES ON LINEAR TRANSFORMATIONS
NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all
1. Let X and Y be normed spaces and let T B(X, Y ).
Uppsala Universitet Matematiska Institutionen Andreas Strömbergsson Prov i matematik Funktionalanalys Kurs: NVP, Frist. 2005-03-14 Skrivtid: 9 11.30 Tillåtna hjälpmedel: Manuella skrivdon, Kreyszigs bok
Practice with Proofs
Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using
Follow links for Class Use and other Permissions. For more information send email to: [email protected]
COPYRIGHT NOTICE: Ariel Rubinstein: Lecture Notes in Microeconomic Theory is published by Princeton University Press and copyrighted, c 2006, by Princeton University Press. All rights reserved. No part
1 Completeness of a Set of Eigenfunctions. Lecturer: Naoki Saito Scribe: Alexander Sheynis/Allen Xue. May 3, 2007. 1.1 The Neumann Boundary Condition
MAT 280: Laplacian Eigenfunctions: Theory, Applications, and Computations Lecture 11: Laplacian Eigenvalue Problems for General Domains III. Completeness of a Set of Eigenfunctions and the Justification
a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.
Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given
Date: April 12, 2001. Contents
2 Lagrange Multipliers Date: April 12, 2001 Contents 2.1. Introduction to Lagrange Multipliers......... p. 2 2.2. Enhanced Fritz John Optimality Conditions...... p. 12 2.3. Informative Lagrange Multipliers...........
Pacific Journal of Mathematics
Pacific Journal of Mathematics GLOBAL EXISTENCE AND DECREASING PROPERTY OF BOUNDARY VALUES OF SOLUTIONS TO PARABOLIC EQUATIONS WITH NONLOCAL BOUNDARY CONDITIONS Sangwon Seo Volume 193 No. 1 March 2000
Research Article Stability Analysis for Higher-Order Adjacent Derivative in Parametrized Vector Optimization
Hindawi Publishing Corporation Journal of Inequalities and Applications Volume 2010, Article ID 510838, 15 pages doi:10.1155/2010/510838 Research Article Stability Analysis for Higher-Order Adjacent Derivative
4. Expanding dynamical systems
4.1. Metric definition. 4. Expanding dynamical systems Definition 4.1. Let X be a compact metric space. A map f : X X is said to be expanding if there exist ɛ > 0 and L > 1 such that d(f(x), f(y)) Ld(x,
UNIVERSITETET I OSLO
NIVERSITETET I OSLO Det matematisk-naturvitenskapelige fakultet Examination in: Trial exam Partial differential equations and Sobolev spaces I. Day of examination: November 18. 2009. Examination hours:
CHAPTER IV - BROWNIAN MOTION
CHAPTER IV - BROWNIAN MOTION JOSEPH G. CONLON 1. Construction of Brownian Motion There are two ways in which the idea of a Markov chain on a discrete state space can be generalized: (1) The discrete time
MA651 Topology. Lecture 6. Separation Axioms.
MA651 Topology. Lecture 6. Separation Axioms. This text is based on the following books: Fundamental concepts of topology by Peter O Neil Elements of Mathematics: General Topology by Nicolas Bourbaki Counterexamples
Solving Linear Systems, Continued and The Inverse of a Matrix
, Continued and The of a Matrix Calculus III Summer 2013, Session II Monday, July 15, 2013 Agenda 1. The rank of a matrix 2. The inverse of a square matrix Gaussian Gaussian solves a linear system by reducing
α = u v. In other words, Orthogonal Projection
Orthogonal Projection Given any nonzero vector v, it is possible to decompose an arbitrary vector u into a component that points in the direction of v and one that points in a direction orthogonal to v
Chapter 5. Banach Spaces
9 Chapter 5 Banach Spaces Many linear equations may be formulated in terms of a suitable linear operator acting on a Banach space. In this chapter, we study Banach spaces and linear operators acting on
Sample Induction Proofs
Math 3 Worksheet: Induction Proofs III, Sample Proofs A.J. Hildebrand Sample Induction Proofs Below are model solutions to some of the practice problems on the induction worksheets. The solutions given
Limits and Continuity
Math 20C Multivariable Calculus Lecture Limits and Continuity Slide Review of Limit. Side limits and squeeze theorem. Continuous functions of 2,3 variables. Review: Limits Slide 2 Definition Given a function
Inner Product Spaces
Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and
1 if 1 x 0 1 if 0 x 1
Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or
MATH10040 Chapter 2: Prime and relatively prime numbers
MATH10040 Chapter 2: Prime and relatively prime numbers Recall the basic definition: 1. Prime numbers Definition 1.1. Recall that a positive integer is said to be prime if it has precisely two positive
The Ergodic Theorem and randomness
The Ergodic Theorem and randomness Peter Gács Department of Computer Science Boston University March 19, 2008 Peter Gács (Boston University) Ergodic theorem March 19, 2008 1 / 27 Introduction Introduction
1 = (a 0 + b 0 α) 2 + + (a m 1 + b m 1 α) 2. for certain elements a 0,..., a m 1, b 0,..., b m 1 of F. Multiplying out, we obtain
Notes on real-closed fields These notes develop the algebraic background needed to understand the model theory of real-closed fields. To understand these notes, a standard graduate course in algebra is
MEASURE AND INTEGRATION. Dietmar A. Salamon ETH Zürich
MEASURE AND INTEGRATION Dietmar A. Salamon ETH Zürich 12 May 2016 ii Preface This book is based on notes for the lecture course Measure and Integration held at ETH Zürich in the spring semester 2014. Prerequisites
DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents
DIFFERENTIABILITY OF COMPLEX FUNCTIONS Contents 1. Limit definition of a derivative 1 2. Holomorphic functions, the Cauchy-Riemann equations 3 3. Differentiability of real functions 5 4. A sufficient condition
Section 4.4 Inner Product Spaces
Section 4.4 Inner Product Spaces In our discussion of vector spaces the specific nature of F as a field, other than the fact that it is a field, has played virtually no role. In this section we no longer
FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z
FACTORING POLYNOMIALS IN THE RING OF FORMAL POWER SERIES OVER Z DANIEL BIRMAJER, JUAN B GIL, AND MICHAEL WEINER Abstract We consider polynomials with integer coefficients and discuss their factorization
Section 6.1 - Inner Products and Norms
Section 6.1 - Inner Products and Norms Definition. Let V be a vector space over F {R, C}. An inner product on V is a function that assigns, to every ordered pair of vectors x and y in V, a scalar in F,
Unified Lecture # 4 Vectors
Fall 2005 Unified Lecture # 4 Vectors These notes were written by J. Peraire as a review of vectors for Dynamics 16.07. They have been adapted for Unified Engineering by R. Radovitzky. References [1] Feynmann,
x a x 2 (1 + x 2 ) n.
Limits and continuity Suppose that we have a function f : R R. Let a R. We say that f(x) tends to the limit l as x tends to a; lim f(x) = l ; x a if, given any real number ɛ > 0, there exists a real number
TOPIC 4: DERIVATIVES
TOPIC 4: DERIVATIVES 1. The derivative of a function. Differentiation rules 1.1. The slope of a curve. The slope of a curve at a point P is a measure of the steepness of the curve. If Q is a point on the
16.3 Fredholm Operators
Lectures 16 and 17 16.3 Fredholm Operators A nice way to think about compact operators is to show that set of compact operators is the closure of the set of finite rank operator in operator norm. In this
Math 319 Problem Set #3 Solution 21 February 2002
Math 319 Problem Set #3 Solution 21 February 2002 1. ( 2.1, problem 15) Find integers a 1, a 2, a 3, a 4, a 5 such that every integer x satisfies at least one of the congruences x a 1 (mod 2), x a 2 (mod
1 The Brownian bridge construction
The Brownian bridge construction The Brownian bridge construction is a way to build a Brownian motion path by successively adding finer scale detail. This construction leads to a relatively easy proof
Adaptive Online Gradient Descent
Adaptive Online Gradient Descent Peter L Bartlett Division of Computer Science Department of Statistics UC Berkeley Berkeley, CA 94709 bartlett@csberkeleyedu Elad Hazan IBM Almaden Research Center 650
CITY UNIVERSITY LONDON. BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION
No: CITY UNIVERSITY LONDON BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION ENGINEERING MATHEMATICS 2 (resit) EX2005 Date: August
Mathematical Methods of Engineering Analysis
Mathematical Methods of Engineering Analysis Erhan Çinlar Robert J. Vanderbei February 2, 2000 Contents Sets and Functions 1 1 Sets................................... 1 Subsets.............................
3. Mathematical Induction
3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)
Geometrical Characterization of RN-operators between Locally Convex Vector Spaces
Geometrical Characterization of RN-operators between Locally Convex Vector Spaces OLEG REINOV St. Petersburg State University Dept. of Mathematics and Mechanics Universitetskii pr. 28, 198504 St, Petersburg
GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH
GENTLY KILLING S SPACES TODD EISWORTH, PETER NYIKOS, AND SAHARON SHELAH Abstract. We produce a model of ZFC in which there are no locally compact first countable S spaces, and in which 2 ℵ 0 < 2 ℵ 1. A
Class Meeting # 1: Introduction to PDEs
MATH 18.152 COURSE NOTES - CLASS MEETING # 1 18.152 Introduction to PDEs, Fall 2011 Professor: Jared Speck Class Meeting # 1: Introduction to PDEs 1. What is a PDE? We will be studying functions u = u(x
ALMOST COMMON PRIORS 1. INTRODUCTION
ALMOST COMMON PRIORS ZIV HELLMAN ABSTRACT. What happens when priors are not common? We introduce a measure for how far a type space is from having a common prior, which we term prior distance. If a type
t := maxγ ν subject to ν {0,1,2,...} and f(x c +γ ν d) f(x c )+cγ ν f (x c ;d).
1. Line Search Methods Let f : R n R be given and suppose that x c is our current best estimate of a solution to P min x R nf(x). A standard method for improving the estimate x c is to choose a direction
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 3 Binary Operations We are used to addition and multiplication of real numbers. These operations combine two real numbers
8 Divisibility and prime numbers
8 Divisibility and prime numbers 8.1 Divisibility In this short section we extend the concept of a multiple from the natural numbers to the integers. We also summarize several other terms that express
Continuity of the Perron Root
Linear and Multilinear Algebra http://dx.doi.org/10.1080/03081087.2014.934233 ArXiv: 1407.7564 (http://arxiv.org/abs/1407.7564) Continuity of the Perron Root Carl D. Meyer Department of Mathematics, North
T ( a i x i ) = a i T (x i ).
Chapter 2 Defn 1. (p. 65) Let V and W be vector spaces (over F ). We call a function T : V W a linear transformation form V to W if, for all x, y V and c F, we have (a) T (x + y) = T (x) + T (y) and (b)
MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets.
MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. Norm The notion of norm generalizes the notion of length of a vector in R n. Definition. Let V be a vector space. A function α
Parabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation
7 5.1 Definitions Properties Chapter 5 Parabolic Equations Note that we require the solution u(, t bounded in R n for all t. In particular we assume that the boundedness of the smooth function u at infinity
v w is orthogonal to both v and w. the three vectors v, w and v w form a right-handed set of vectors.
3. Cross product Definition 3.1. Let v and w be two vectors in R 3. The cross product of v and w, denoted v w, is the vector defined as follows: the length of v w is the area of the parallelogram with
ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING. 0. Introduction
ON SEQUENTIAL CONTINUITY OF COMPOSITION MAPPING Abstract. In [1] there was proved a theorem concerning the continuity of the composition mapping, and there was announced a theorem on sequential continuity
10.2 Series and Convergence
10.2 Series and Convergence Write sums using sigma notation Find the partial sums of series and determine convergence or divergence of infinite series Find the N th partial sums of geometric series and
Walrasian Demand. u(x) where B(p, w) = {x R n + : p x w}.
Walrasian Demand Econ 2100 Fall 2015 Lecture 5, September 16 Outline 1 Walrasian Demand 2 Properties of Walrasian Demand 3 An Optimization Recipe 4 First and Second Order Conditions Definition Walrasian
NONLOCAL PROBLEMS WITH NEUMANN BOUNDARY CONDITIONS
NONLOCAL PROBLEMS WITH NEUMANN BOUNDARY CONDITIONS SERENA DIPIERRO, XAVIER ROS-OTON, AND ENRICO VALDINOCI Abstract. We introduce a new Neumann problem for the fractional Laplacian arising from a simple
Linear Algebra I. Ronald van Luijk, 2012
Linear Algebra I Ronald van Luijk, 2012 With many parts from Linear Algebra I by Michael Stoll, 2007 Contents 1. Vector spaces 3 1.1. Examples 3 1.2. Fields 4 1.3. The field of complex numbers. 6 1.4.
Every Positive Integer is the Sum of Four Squares! (and other exciting problems)
Every Positive Integer is the Sum of Four Squares! (and other exciting problems) Sophex University of Texas at Austin October 18th, 00 Matilde N. Lalín 1. Lagrange s Theorem Theorem 1 Every positive integer
Stochastic Inventory Control
Chapter 3 Stochastic Inventory Control 1 In this chapter, we consider in much greater details certain dynamic inventory control problems of the type already encountered in section 1.3. In addition to the
4 Lyapunov Stability Theory
4 Lyapunov Stability Theory In this section we review the tools of Lyapunov stability theory. These tools will be used in the next section to analyze the stability properties of a robot controller. We
ON NONNEGATIVE SOLUTIONS OF NONLINEAR TWO-POINT BOUNDARY VALUE PROBLEMS FOR TWO-DIMENSIONAL DIFFERENTIAL SYSTEMS WITH ADVANCED ARGUMENTS
ON NONNEGATIVE SOLUTIONS OF NONLINEAR TWO-POINT BOUNDARY VALUE PROBLEMS FOR TWO-DIMENSIONAL DIFFERENTIAL SYSTEMS WITH ADVANCED ARGUMENTS I. KIGURADZE AND N. PARTSVANIA A. Razmadze Mathematical Institute
Modern Optimization Methods for Big Data Problems MATH11146 The University of Edinburgh
Modern Optimization Methods for Big Data Problems MATH11146 The University of Edinburgh Peter Richtárik Week 3 Randomized Coordinate Descent With Arbitrary Sampling January 27, 2016 1 / 30 The Problem
6.2 Permutations continued
6.2 Permutations continued Theorem A permutation on a finite set A is either a cycle or can be expressed as a product (composition of disjoint cycles. Proof is by (strong induction on the number, r, of
6 Commutators and the derived series. [x,y] = xyx 1 y 1.
6 Commutators and the derived series Definition. Let G be a group, and let x,y G. The commutator of x and y is [x,y] = xyx 1 y 1. Note that [x,y] = e if and only if xy = yx (since x 1 y 1 = (yx) 1 ). Proposition
k, then n = p2α 1 1 pα k
Powers of Integers An integer n is a perfect square if n = m for some integer m. Taking into account the prime factorization, if m = p α 1 1 pα k k, then n = pα 1 1 p α k k. That is, n is a perfect square
Taylor and Maclaurin Series
Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions
Lecture L3 - Vectors, Matrices and Coordinate Transformations
S. Widnall 16.07 Dynamics Fall 2009 Lecture notes based on J. Peraire Version 2.0 Lecture L3 - Vectors, Matrices and Coordinate Transformations By using vectors and defining appropriate operations between
