CONVEXITY OF INVERSION FOR POSITIVE OPERATORS ON A HILBERT SPACE. Sangadji *

Size: px
Start display at page:

Download "CONVEXITY OF INVERSION FOR POSITIVE OPERATORS ON A HILBERT SPACE. Sangadji *"

Transcription

1 CONVEXITY OF INVERSION FOR POSITIVE OPERTORS ON HILBERT SPCE Sangadji * BSTRK KONVEKSITS DRI INVERSI UNTUK OPERTOR-OPERTOR POSITIF PD RUNG HILBERT Makalah ini membahas dan membuktikan tiga teorema tentang operator-operator invertibel positif pada ruang Hilbert Teorema pertama memberikan suatu perbandingan dari nilai rerata aritmetika tergeneralisir, nilai rerata geometri tergeneralisir, dan nilai rerata harmonik tergeneralisir untuk operator-operator invertibel positif pada ruang Hilbert Untuk teorema kedua dan ketiga masing-masing memberikan tiga pertaksamaan untuk operator-operator invertibel positif pada ruang Hilbert yang ketiganya ekivalen BSTRCT CONVEXITY OF INVERSION FOR POSITIVE OPERTORS ON HILBERT SPCE This paper discusses and proves three theorems for positive invertible operators on a Hilbert space The first theorem gives a comparison of the generalized arithmetic mean, generalized geometric mean, and generalized harmonic mean for positive invertible operators on a Hilbert space For the second and third theorems each gives three inequalities for positive invertible operators on a Hilbert space that are mutually equivalent PRELIMINRIES Let X be a real or complex vector space norm on X is a non-negative real valued function L on X such that for all scalar and all x, y X the following hold: ( i x 0 x = 0 x = 0 ( ii x + y x + y ( iii x = x * Pusat Pengembangan Teknologi Informasi dan Komputasi - TN

2 real (complex normed linear space is a real (complex vector space X together with specified norm on X On such a space we have a metric ρ defined by ρ ( x, y = x y If X is complete in this metric we call X a Banach space Completeness means that if x is a sequence of elements of X such that { } n there exists an element x in X such that lim x m xn = m, n lim x x = 0 n (, Let H be a real or complex vector space n inner product on H is a function which assigns to each ordered pair of vectors in H a scalar, in such a way that for all x, y, z H and all scalar the following hold: ( i ( x + y, z = ( x, z + ( y, z ( ii ( iii ( x, y = ( x, y ( x, y = ( y, x ( iv ( x, x 0 ( x, x = 0 x = 0 Such a space H, together with a specified inner product on H, is called an inner product space In any inner product space H we have the Cauchy-Schwarz inequality: From the Cauchy-Schwarz inequality it follows that n ( x, y ( x, x( y, y, for all x, y H 0 1 / x = ( x, x constitutes a norm on H If H is complete in this norm, we call that H is a Hilbert space function f defined on a set S is called to be convex if for each x, y S and each, 0 1 we have f ( x + (1 y f ( x + (1 f ( y n operator on a Hilbert space H is called to be positive if ( x > 0 for every x H If T is a positive operator on H then for real numbers, β we define the operator T + β on H by ( T + β ( x = T( x + β, x H MIN RESULT The main result of this paper are the following three theorems The first one gives a comparison of the generalized arithmetic mean, generalized geometric mean, and generalized harmonic mean for positive invertible operators on a Hilbert space

3 For the second and third theorems each gives three inequalities for positive invertible operators on a Hilbert space that are mutually equivalent Theorem 1 Let and B be positive invertible operators on a Hilbert space H Then for 0 1 the following inequalities hold: (1 ( B 1 [(1 ] 1 / / / 1 / (1 Proof Consider the function F( x = x + 1 x for positive real numbers x and 0 1 First we need to show that F (x is a nonnegative function on the interval [ 0, Recall that F (x is continuous on [ 0, By routine calculation we get F (0 = 1 0, F(1 = 0, F'( x = (1 x and F'( x = (1 x 0, 0 x 1, F'( x = (1 x 0, 1 x < Thus we have that F (x is monotonically decreasing on [ 0,1] with 0 F( x 1 and monotonically increasing on [ 1, with F ( x 0 Since F (x is a nonnegative function on the interval, by the standard operational calculus we have for a positive operator T on H and 0 1: T + 1 T ( By replacing T with T -1 in ( we get T + 1 T, (3 and by taking inverses of both sides (3 we get T ( T + 1 (4 Combining ( and (4 we conclude T + 1 T ( T + 1 (5

4 / / Putting T = B in (5 we have + 1 ( [ ( + 1 ] (6 Finally, multiplying by 1 / on both sides in (6 we achieve 1/ 1/ 1/ B + ( [ ( + 1 ] / 1/ B + ( ( B + (1 ( 1/ 1 B 1 [(1 ] 1 / / / 1 /,, Theorem Let T be a positive invertible operator on a Hilbert space H Then the following hold and are mutually equivalent: ( i If 1 0 then T + 1 T ( ii if ( iii if > 1 then T + 1 T < 0 then T + 1 T (7 Proof Obviously assertion (i was already obtained in ( The rest is to show the equivalence of (i, (ii and (iii ( i ( ii : ssume > 1 ssertion (i is equivalent to 1 / 1 / S (1/ S + 1 (1/, ie, S S + Putting 1 / T = S we have T S + 1 Thus (i implies (ii Similarly we can get (ii implies (i ( ii ( iii : ssertion (ii is equivalent to S + 1 S Multiply both / sides of this inequality by S to obtain the equivalent inequality 1 (1 + S S b for any > 1 Then set λ = 1 < 0 and T = S We λ get λt + 1 λ T Thus (ii implies (iii Similarly we can get (iii implies (ii

5 Theorem 3 Let and B be positive invertible operators on a Hilbert space H Then the following hold and are mutually equivalent: 1 / / / 1 / ( i If 1 0 then (1 ( ( ii ( iii if > 1 then (1 1 / if < 0 then (1 ( 1 / / ( / / / 1 / 1 / (8 Proof / / Use Theorem by putting T = we have ( i If 1 0 then + 1 ( ( ii if > 1then ( iii if < 0 then + 1 ( + 1 ( (9 1 / and then multiplying (9 by on both sides we get 1/ ( i If 1 0 then (1 ( ( ii if > 1then (1 1/ ( iii if < 0 then (1 as desired ( 1/ ( 1/ 1/ 1/ CONCLUSION Inequalities in (5 are very important and fundamental Inequalities in (1 in / / Theorem 1 can be obtained from (5 by putting T = B Statements in Theorem can be derived from the first inequality in (5 Statements in Theorem 3 / / obviously can be derived from statements in Theorem by putting T = 1 / and then multiplying by on both sides

6 REFERENCES 1 HOFFMN, K, Banach Spaces of nalytic Functions, Dover Publications, Inc, New York (196 WNG, D Convex Operator Function, Internat J Math nd Sci 11 ( FURUT, T and YNGID, M, Generalized Means and Convexity of Inversion for Positive Operators, The merican Mathematical Monthly, Volume 105, Numbert 3 The Mathematical ssociation of merica (1998

Projection Theorem 1

Projection Theorem 1 Projection Theorem 1 Cauchy-Schwarz Inequality Lemma. (Cauchy-Schwarz Inequality) For all x, y in an inner product space, [ xy, ] x y. Equality holds if and only if x y or y θ. Proof. If y θ, the inequality

More information

Orthonormal Bases Fall Consider an inner product space V with inner product f, g and norm

Orthonormal Bases Fall Consider an inner product space V with inner product f, g and norm 8.03 Fall 203 Orthonormal Bases Consider an inner product space V with inner product f, g and norm f 2 = f, f Proposition (Continuity) If u n u 0 and v n v 0 as n, then u n u ; u n, v n u, v. Proof. Note

More information

Applied Linear Algebra in Geoscience Using MATLAB

Applied Linear Algebra in Geoscience Using MATLAB Applied Linear Algebra in Geoscience Using MATLAB Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots Programming in

More information

Chapter 2. Vectors and Vector Spaces

Chapter 2. Vectors and Vector Spaces 2.1. Operations on Vectors 1 Chapter 2. Vectors and Vector Spaces Section 2.1. Operations on Vectors Note. In this section, we define several arithmetic operations on vectors (especially, vector addition

More information

INNER PRODUCT SPACE. Definition 1

INNER PRODUCT SPACE. Definition 1 INNER PRODUCT SPACE Definition 1 Suppose u, v and w are all vectors in vector space V and c is any scalar. An inner product space on the vectors space V is a function that associates with each pair of

More information

MAT 771 FUNCTIONAL ANALYSIS HOMEWORK 3. (1) Let V be the vector space of all bounded or unbounded sequences of complex numbers.

MAT 771 FUNCTIONAL ANALYSIS HOMEWORK 3. (1) Let V be the vector space of all bounded or unbounded sequences of complex numbers. MAT 771 FUNCTIONAL ANALYSIS HOMEWORK 3 (1) Let V be the vector space of all bounded or unbounded sequences of complex numbers. (a) Define d : V V + {0} by d(x, y) = 1 ξ j η j 2 j 1 + ξ j η j. Show that

More information

MA677 Assignment #3 Morgan Schreffler Due 09/19/12 Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1:

MA677 Assignment #3 Morgan Schreffler Due 09/19/12 Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1: Exercise 1 Using Hölder s inequality, prove Minkowski s inequality for f, g L p (R d ), p 1: f + g p f p + g p. Proof. If f, g L p (R d ), then since f(x) + g(x) max {f(x), g(x)}, we have f(x) + g(x) p

More information

Contents. 2 Sequences and Series Approximation by Rational Numbers Sequences Basics on Sequences...

Contents. 2 Sequences and Series Approximation by Rational Numbers Sequences Basics on Sequences... Contents 1 Real Numbers: The Basics... 1 1.1 Notation... 1 1.2 Natural Numbers... 4 1.3 Integers... 5 1.4 Fractions and Rational Numbers... 10 1.4.1 Introduction... 10 1.4.2 Powers and Radicals of Rational

More information

2-FARTHEST ORTHOGONALITY IN GENERALIZED 2-NORMED SPACES

2-FARTHEST ORTHOGONALITY IN GENERALIZED 2-NORMED SPACES J. Indones. Math. Soc. Vol. 24, No. 1 (2018), pp. 71 78. 2-FARTHEST ORTHOGONALITY IN GENERALIZED 2-NORMED SPACES S. M. Mousav Shams Abad 1, H. Mazaheri 2, and M. A. Dehghan 3 1 Faculty of Mathematics,

More information

CHAPTER II HILBERT SPACES

CHAPTER II HILBERT SPACES CHAPTER II HILBERT SPACES 2.1 Geometry of Hilbert Spaces Definition 2.1.1. Let X be a complex linear space. An inner product on X is a function, : X X C which satisfies the following axioms : 1. y, x =

More information

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define Homework, Real Analysis I, Fall, 2010. (1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define ρ(f, g) = 1 0 f(x) g(x) dx. Show that

More information

An introduction to some aspects of functional analysis

An introduction to some aspects of functional analysis An introduction to some aspects of functional analysis Stephen Semmes Rice University Abstract These informal notes deal with some very basic objects in functional analysis, including norms and seminorms

More information

The Gram matrix in inner product modules over C -algebras

The Gram matrix in inner product modules over C -algebras The Gram matrix in inner product modules over C -algebras Ljiljana Arambašić (joint work with D. Bakić and M.S. Moslehian) Department of Mathematics University of Zagreb Applied Linear Algebra May 24 28,

More information

11.1 Vectors in the plane

11.1 Vectors in the plane 11.1 Vectors in the plane What is a vector? It is an object having direction and length. Geometric way to represent vectors It is represented by an arrow. The direction of the arrow is the direction of

More information

The Transpose of a Vector

The Transpose of a Vector 8 CHAPTER Vectors The Transpose of a Vector We now consider the transpose of a vector in R n, which is a row vector. For a vector u 1 u. u n the transpose is denoted by u T = [ u 1 u u n ] EXAMPLE -5 Find

More information

ABSTRACT CONDITIONAL EXPECTATION IN L 2

ABSTRACT CONDITIONAL EXPECTATION IN L 2 ABSTRACT CONDITIONAL EXPECTATION IN L 2 Abstract. We prove that conditional expecations exist in the L 2 case. The L 2 treatment also gives us a geometric interpretation for conditional expectation. 1.

More information

NORMS ON SPACE OF MATRICES

NORMS ON SPACE OF MATRICES NORMS ON SPACE OF MATRICES. Operator Norms on Space of linear maps Let A be an n n real matrix and x 0 be a vector in R n. We would like to use the Picard iteration method to solve for the following system

More information

SEMI-INNER PRODUCTS AND THE NUMERICAL RADIUS OF BOUNDED LINEAR OPERATORS IN HILBERT SPACES

SEMI-INNER PRODUCTS AND THE NUMERICAL RADIUS OF BOUNDED LINEAR OPERATORS IN HILBERT SPACES SEMI-INNER PRODUCTS AND THE NUMERICAL RADIUS OF BOUNDED LINEAR OPERATORS IN HILBERT SPACES S.S. DRAGOMIR Abstract. The main aim of this paper is to establish some connections that exist between the numerical

More information

Spectral Theory, with an Introduction to Operator Means. William L. Green

Spectral Theory, with an Introduction to Operator Means. William L. Green Spectral Theory, with an Introduction to Operator Means William L. Green January 30, 2008 Contents Introduction............................... 1 Hilbert Space.............................. 4 Linear Maps

More information

TWO ASPECTS OF A GENERALIZED FIBONACCI SEQUENCE

TWO ASPECTS OF A GENERALIZED FIBONACCI SEQUENCE J. Indones. Math. Soc. Vol., No. (05, pp. 7. TWO ASPECTS OF A GENERALIZED FIBONACCI SEQUENCE J.M. Tuwankotta Analysis and Geometry Group, FMIPA, Institut Teknologi Bandung, Ganesha no. 0, Bandung, Indonesia

More information

LEBESGUE MEASURE AND L2 SPACE. Contents 1. Measure Spaces 1 2. Lebesgue Integration 2 3. L 2 Space 4 Acknowledgments 9 References 9

LEBESGUE MEASURE AND L2 SPACE. Contents 1. Measure Spaces 1 2. Lebesgue Integration 2 3. L 2 Space 4 Acknowledgments 9 References 9 LBSGU MASUR AND L2 SPAC. ANNI WANG Abstract. This paper begins with an introduction to measure spaces and the Lebesgue theory of measure and integration. Several important theorems regarding the Lebesgue

More information

4 Linear operators and linear functionals

4 Linear operators and linear functionals 4 Linear operators and linear functionals The next section is devoted to studying linear operators between normed spaces. Definition 4.1. Let V and W be normed spaces over a field F. We say that T : V

More information

Lecture 5. Ch. 5, Norms for vectors and matrices. Norms for vectors and matrices Why?

Lecture 5. Ch. 5, Norms for vectors and matrices. Norms for vectors and matrices Why? KTH ROYAL INSTITUTE OF TECHNOLOGY Norms for vectors and matrices Why? Lecture 5 Ch. 5, Norms for vectors and matrices Emil Björnson/Magnus Jansson/Mats Bengtsson April 27, 2016 Problem: Measure size of

More information

6 Inner Product and Hilbert Spaces

6 Inner Product and Hilbert Spaces 6 Inner Product and Hilbert Spaces 6. Motivation Of the different p-norms on R n, p = 2 is special. This is because the 2-norm (λ, λ 2,..., λ n ) 2 = λ 2 + λ2 2 + + λ2 n comes from the an inner product

More information

Math 209B Homework 2

Math 209B Homework 2 Math 29B Homework 2 Edward Burkard Note: All vector spaces are over the field F = R or C 4.6. Two Compactness Theorems. 4. Point Set Topology Exercise 6 The product of countably many sequentally compact

More information

[Lihat sebelah 50/2 SULIT

[Lihat sebelah 50/2 SULIT SULIT 5 50/ For Examiner s Use [Lihat sebelah 50/ SULIT For examiner s use SULIT 6 50/ Answer all questions. Jawab semua soalan. 1 Calculate the value of 15 4. Hitung nilai bagi 15 4. [ marks] [ markah]

More information

Remarks on the Spectrum of Bounded and Normal Operators on Hilbert Spaces

Remarks on the Spectrum of Bounded and Normal Operators on Hilbert Spaces An. Şt. Univ. Ovidius Constanţa Vol. 16(2), 2008, 7 14 Remarks on the Spectrum of Bounded and Normal Operators on Hilbert Spaces M. AKKOUCHI Abstract Let H be a complex Hilbert space H. Let T be a bounded

More information

Prof. M. Saha Professor of Mathematics The University of Burdwan West Bengal, India

Prof. M. Saha Professor of Mathematics The University of Burdwan West Bengal, India CHAPTER 9 BY Prof. M. Saha Professor of Mathematics The University of Burdwan West Bengal, India E-mail : mantusaha.bu@gmail.com Introduction and Objectives In the preceding chapters, we discussed normed

More information

Vector spaces. DS-GA 1013 / MATH-GA 2824 Optimization-based Data Analysis.

Vector spaces. DS-GA 1013 / MATH-GA 2824 Optimization-based Data Analysis. Vector spaces DS-GA 1013 / MATH-GA 2824 Optimization-based Data Analysis http://www.cims.nyu.edu/~cfgranda/pages/obda_fall17/index.html Carlos Fernandez-Granda Vector space Consists of: A set V A scalar

More information

The spectrum of a self-adjoint operator is a compact subset of R

The spectrum of a self-adjoint operator is a compact subset of R The spectrum of a self-adjoint operator is a compact subset of R Jordan Bell jordan.bell@gmail.com Department of Mathematics, University of Toronto April 3, 2014 Abstract In these notes I prove that the

More information

AN ELEMENTARY PROOF OF THE SPECTRAL RADIUS FORMULA FOR MATRICES

AN ELEMENTARY PROOF OF THE SPECTRAL RADIUS FORMULA FOR MATRICES AN ELEMENTARY PROOF OF THE SPECTRAL RADIUS FORMULA FOR MATRICES JOEL A. TROPP Abstract. We present an elementary proof that the spectral radius of a matrix A may be obtained using the formula ρ(a) lim

More information

Problem Set 1: Solutions Math 201A: Fall Problem 1. Let (X, d) be a metric space. (a) Prove the reverse triangle inequality: for every x, y, z X

Problem Set 1: Solutions Math 201A: Fall Problem 1. Let (X, d) be a metric space. (a) Prove the reverse triangle inequality: for every x, y, z X Problem Set 1: s Math 201A: Fall 2016 Problem 1. Let (X, d) be a metric space. (a) Prove the reverse triangle inequality: for every x, y, z X d(x, y) d(x, z) d(z, y). (b) Prove that if x n x and y n y

More information

1 Inner Product Space

1 Inner Product Space Ch - Hilbert Space 1 4 Hilbert Space 1 Inner Product Space Let E be a complex vector space, a mapping (, ) : E E C is called an inner product on E if i) (x, x) 0 x E and (x, x) = 0 if and only if x = 0;

More information

Normed & Inner Product Vector Spaces

Normed & Inner Product Vector Spaces Normed & Inner Product Vector Spaces ECE 174 Introduction to Linear & Nonlinear Optimization Ken Kreutz-Delgado ECE Department, UC San Diego Ken Kreutz-Delgado (UC San Diego) ECE 174 Fall 2016 1 / 27 Normed

More information

Fourier and Wavelet Signal Processing

Fourier and Wavelet Signal Processing Ecole Polytechnique Federale de Lausanne (EPFL) Audio-Visual Communications Laboratory (LCAV) Fourier and Wavelet Signal Processing Martin Vetterli Amina Chebira, Ali Hormati Spring 2011 2/25/2011 1 Outline

More information

Advanced Analysis Qualifying Examination Department of Mathematics and Statistics University of Massachusetts. Monday, August 26, 2013

Advanced Analysis Qualifying Examination Department of Mathematics and Statistics University of Massachusetts. Monday, August 26, 2013 NAME: Advanced Analysis Qualifying Examination Department of Mathematics and Statistics University of Massachusetts Monday, August 26, 2013 Instructions 1. This exam consists of eight (8) problems all

More information

CLOSED RANGE POSITIVE OPERATORS ON BANACH SPACES

CLOSED RANGE POSITIVE OPERATORS ON BANACH SPACES Acta Math. Hungar., 142 (2) (2014), 494 501 DOI: 10.1007/s10474-013-0380-2 First published online December 11, 2013 CLOSED RANGE POSITIVE OPERATORS ON BANACH SPACES ZS. TARCSAY Department of Applied Analysis,

More information

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space

PROBLEMS. (b) (Polarization Identity) Show that in any inner product space 1 Professor Carl Cowen Math 54600 Fall 09 PROBLEMS 1. (Geometry in Inner Product Spaces) (a) (Parallelogram Law) Show that in any inner product space x + y 2 + x y 2 = 2( x 2 + y 2 ). (b) (Polarization

More information

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product

Finite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product Chapter 4 Hilbert Spaces 4.1 Inner Product Spaces Inner Product Space. A complex vector space E is called an inner product space (or a pre-hilbert space, or a unitary space) if there is a mapping (, )

More information

Completion Date: Monday February 11, 2008

Completion Date: Monday February 11, 2008 MATH 4 (R) Winter 8 Intermediate Calculus I Solutions to Problem Set #4 Completion Date: Monday February, 8 Department of Mathematical and Statistical Sciences University of Alberta Question. [Sec..9,

More information

4 Expectation & the Lebesgue Theorems

4 Expectation & the Lebesgue Theorems STA 205: Probability & Measure Theory Robert L. Wolpert 4 Expectation & the Lebesgue Theorems Let X and {X n : n N} be random variables on a probability space (Ω,F,P). If X n (ω) X(ω) for each ω Ω, does

More information

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books.

Applied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books. Applied Analysis APPM 44: Final exam 1:3pm 4:pm, Dec. 14, 29. Closed books. Problem 1: 2p Set I = [, 1]. Prove that there is a continuous function u on I such that 1 ux 1 x sin ut 2 dt = cosx, x I. Define

More information

Intertibility and spectrum of the multiplication operator on the space of square-summable sequences

Intertibility and spectrum of the multiplication operator on the space of square-summable sequences Intertibility and spectrum of the multiplication operator on the space of square-summable sequences Objectives Establish an invertibility criterion and calculate the spectrum of the multiplication operator

More information

HILBERT SPACES AND THE RADON-NIKODYM THEOREM. where the bar in the first equation denotes complex conjugation. In either case, for any x V define

HILBERT SPACES AND THE RADON-NIKODYM THEOREM. where the bar in the first equation denotes complex conjugation. In either case, for any x V define HILBERT SPACES AND THE RADON-NIKODYM THEOREM STEVEN P. LALLEY 1. DEFINITIONS Definition 1. A real inner product space is a real vector space V together with a symmetric, bilinear, positive-definite mapping,

More information

ON MATRIX VALUED SQUARE INTEGRABLE POSITIVE DEFINITE FUNCTIONS

ON MATRIX VALUED SQUARE INTEGRABLE POSITIVE DEFINITE FUNCTIONS 1 2 3 ON MATRIX VALUED SQUARE INTERABLE POSITIVE DEFINITE FUNCTIONS HONYU HE Abstract. In this paper, we study matrix valued positive definite functions on a unimodular group. We generalize two important

More information

Homework If the inverse T 1 of a closed linear operator exists, show that T 1 is a closed linear operator.

Homework If the inverse T 1 of a closed linear operator exists, show that T 1 is a closed linear operator. Homework 3 1 If the inverse T 1 of a closed linear operator exists, show that T 1 is a closed linear operator Solution: Assuming that the inverse of T were defined, then we will have to have that D(T 1

More information

Banach Journal of Mathematical Analysis ISSN: (electronic)

Banach Journal of Mathematical Analysis ISSN: (electronic) Banach J Math Anal (009), no, 64 76 Banach Journal of Mathematical Analysis ISSN: 75-8787 (electronic) http://wwwmath-analysisorg ON A GEOMETRIC PROPERTY OF POSITIVE DEFINITE MATRICES CONE MASATOSHI ITO,

More information

THEOREMS, ETC., FOR MATH 515

THEOREMS, ETC., FOR MATH 515 THEOREMS, ETC., FOR MATH 515 Proposition 1 (=comment on page 17). If A is an algebra, then any finite union or finite intersection of sets in A is also in A. Proposition 2 (=Proposition 1.1). For every

More information

MATH 324 Summer 2011 Elementary Number Theory. Notes on Mathematical Induction. Recall the following axiom for the set of integers.

MATH 324 Summer 2011 Elementary Number Theory. Notes on Mathematical Induction. Recall the following axiom for the set of integers. MATH 4 Summer 011 Elementary Number Theory Notes on Mathematical Induction Principle of Mathematical Induction Recall the following axiom for the set of integers. Well-Ordering Axiom for the Integers If

More information

STRONG CONVERGENCE OF AN ITERATIVE METHOD FOR VARIATIONAL INEQUALITY PROBLEMS AND FIXED POINT PROBLEMS

STRONG CONVERGENCE OF AN ITERATIVE METHOD FOR VARIATIONAL INEQUALITY PROBLEMS AND FIXED POINT PROBLEMS ARCHIVUM MATHEMATICUM (BRNO) Tomus 45 (2009), 147 158 STRONG CONVERGENCE OF AN ITERATIVE METHOD FOR VARIATIONAL INEQUALITY PROBLEMS AND FIXED POINT PROBLEMS Xiaolong Qin 1, Shin Min Kang 1, Yongfu Su 2,

More information

Linear Normed Spaces (cont.) Inner Product Spaces

Linear Normed Spaces (cont.) Inner Product Spaces Linear Normed Spaces (cont.) Inner Product Spaces October 6, 017 Linear Normed Spaces (cont.) Theorem A normed space is a metric space with metric ρ(x,y) = x y Note: if x n x then x n x, and if {x n} is

More information

New Nonlinear Four-Step Method for

New Nonlinear Four-Step Method for Matematika, 003, Jilid 19, bil. 1, hlm. 47 56 c Jabatan Matematik, UTM. New Nonlinear Four-Step Method for y = ft, y) Nazeeruddin Yaacob & Phang Chang Department of Mathematics University Teknologi Malaysia

More information

96 CHAPTER 4. HILBERT SPACES. Spaces of square integrable functions. Take a Cauchy sequence f n in L 2 so that. f n f m 1 (b a) f n f m 2.

96 CHAPTER 4. HILBERT SPACES. Spaces of square integrable functions. Take a Cauchy sequence f n in L 2 so that. f n f m 1 (b a) f n f m 2. 96 CHAPTER 4. HILBERT SPACES 4.2 Hilbert Spaces Hilbert Space. An inner product space is called a Hilbert space if it is complete as a normed space. Examples. Spaces of sequences The space l 2 of square

More information

1.4 The Jacobian of a map

1.4 The Jacobian of a map 1.4 The Jacobian of a map Derivative of a differentiable map Let F : M n N m be a differentiable map between two C 1 manifolds. Given a point p M we define the derivative of F at p by df p df (p) : T p

More information

1 The Projection Theorem

1 The Projection Theorem Several Important Theorems by Francis J. Narcowich November, 14 1 The Projection Theorem Let H be a Hilbert space. When V is a finite dimensional subspace of H and f H, we can always find a unique p V

More information

CHAPTER III THE PROOF OF INEQUALITIES

CHAPTER III THE PROOF OF INEQUALITIES CHAPTER III THE PROOF OF INEQUALITIES In this Chapter, the main purpose is to prove four theorems about Hardy-Littlewood- Pólya Inequality and then gives some examples of their application. We will begin

More information

Various proofs of the Cauchy-Schwarz inequality

Various proofs of the Cauchy-Schwarz inequality OCTOGON MATHEMATICAL MAGAZINE Vol 17, No1, April 009, pp 1-9 ISSN 1-5657, ISBN 978-973-8855-5-0, wwwhetfaluro/octogon 1 Various proofs of the Cauchy-Schwarz inequality Hui-Hua Wu and Shanhe Wu 0 ABSTRACT

More information

Another consequence of the Cauchy Schwarz inequality is the continuity of the inner product.

Another consequence of the Cauchy Schwarz inequality is the continuity of the inner product. . Inner product spaces 1 Theorem.1 (Cauchy Schwarz inequality). If X is an inner product space then x,y x y. (.) Proof. First note that 0 u v v u = u v u v Re u,v. (.3) Therefore, Re u,v u v (.) for all

More information

Functional Analysis, Math 7320 Lecture Notes from August taken by Yaofeng Su

Functional Analysis, Math 7320 Lecture Notes from August taken by Yaofeng Su Functional Analysis, Math 7320 Lecture Notes from August 30 2016 taken by Yaofeng Su 1 Essentials of Topology 1.1 Continuity Next we recall a stronger notion of continuity: 1.1.1 Definition. Let (X, d

More information

Functional Analysis, Math 7321 Lecture Notes from April 04, 2017 taken by Chandi Bhandari

Functional Analysis, Math 7321 Lecture Notes from April 04, 2017 taken by Chandi Bhandari Functional Analysis, Math 7321 Lecture Notes from April 0, 2017 taken by Chandi Bhandari Last time:we have completed direct sum decomposition with generalized eigen space. 2. Theorem. Let X be separable

More information

Your first day at work MATH 806 (Fall 2015)

Your first day at work MATH 806 (Fall 2015) Your first day at work MATH 806 (Fall 2015) 1. Let X be a set (with no particular algebraic structure). A function d : X X R is called a metric on X (and then X is called a metric space) when d satisfies

More information

Hardy s Inequality for Functions of Several Complex Variables (Ketidaksamaan Hardy untuk Fungsi Beberapa Pemboleh Ubah Kompleks)

Hardy s Inequality for Functions of Several Complex Variables (Ketidaksamaan Hardy untuk Fungsi Beberapa Pemboleh Ubah Kompleks) Sains Malaysiana 46(9)(2017): 1355 1359 http://dxdoiorg/1017576/jsm-2017-4609-01 Hardy s Inequality for Functions of Several Complex Variables (Ketidaksamaan Hardy untuk Fungsi Beberapa Pemboleh Ubah Kompleks)

More information

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms (February 24, 2017) 08a. Operators on Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/real/notes 2016-17/08a-ops

More information

Inner products. Theorem (basic properties): Given vectors u, v, w in an inner product space V, and a scalar k, the following properties hold:

Inner products. Theorem (basic properties): Given vectors u, v, w in an inner product space V, and a scalar k, the following properties hold: Inner products Definition: An inner product on a real vector space V is an operation (function) that assigns to each pair of vectors ( u, v) in V a scalar u, v satisfying the following axioms: 1. u, v

More information

MATH 650. THE RADON-NIKODYM THEOREM

MATH 650. THE RADON-NIKODYM THEOREM MATH 650. THE RADON-NIKODYM THEOREM This note presents two important theorems in Measure Theory, the Lebesgue Decomposition and Radon-Nikodym Theorem. They are not treated in the textbook. 1. Closed subspaces

More information

Iterative Methods for Eigenvalues of Symmetric Matrices as Fixed Point Theorems

Iterative Methods for Eigenvalues of Symmetric Matrices as Fixed Point Theorems Iterative Methods for Eigenvalues of Symmetric Matrices as Fixed Point Theorems Student: Amanda Schaeffer Sponsor: Wilfred M. Greenlee December 6, 007. The Power Method and the Contraction Mapping Theorem

More information

Homework Assignment #5 Due Wednesday, March 3rd.

Homework Assignment #5 Due Wednesday, March 3rd. Homework Assignment #5 Due Wednesday, March 3rd. 1. In this problem, X will be a separable Banach space. Let B be the closed unit ball in X. We want to work out a solution to E 2.5.3 in the text. Work

More information

5 Compact linear operators

5 Compact linear operators 5 Compact linear operators One of the most important results of Linear Algebra is that for every selfadjoint linear map A on a finite-dimensional space, there exists a basis consisting of eigenvectors.

More information

Math 290, Midterm II-key

Math 290, Midterm II-key Math 290, Midterm II-key Name (Print): (first) Signature: (last) The following rules apply: There are a total of 20 points on this 50 minutes exam. This contains 7 pages (including this cover page) and

More information

THE CYCLIC DOUGLAS RACHFORD METHOD FOR INCONSISTENT FEASIBILITY PROBLEMS

THE CYCLIC DOUGLAS RACHFORD METHOD FOR INCONSISTENT FEASIBILITY PROBLEMS THE CYCLIC DOUGLAS RACHFORD METHOD FOR INCONSISTENT FEASIBILITY PROBLEMS JONATHAN M. BORWEIN AND MATTHEW K. TAM Abstract. We analyse the behaviour of the newly introduced cyclic Douglas Rachford algorithm

More information

Your first day at work MATH 806 (Fall 2015)

Your first day at work MATH 806 (Fall 2015) Your first day at work MATH 806 (Fall 2015) 1. Let X be a set (with no particular algebraic structure). A function d : X X R is called a metric on X (and then X is called a metric space) when d satisfies

More information

Recall that any inner product space V has an associated norm defined by

Recall that any inner product space V has an associated norm defined by Hilbert Spaces Recall that any inner product space V has an associated norm defined by v = v v. Thus an inner product space can be viewed as a special kind of normed vector space. In particular every inner

More information

First In-Class Exam Solutions Math 410, Professor David Levermore Monday, 1 October 2018

First In-Class Exam Solutions Math 410, Professor David Levermore Monday, 1 October 2018 First In-Class Exam Solutions Math 40, Professor David Levermore Monday, October 208. [0] Let {b k } k N be a sequence in R and let A be a subset of R. Write the negations of the following assertions.

More information

SECTION 9.2: ARITHMETIC SEQUENCES and PARTIAL SUMS

SECTION 9.2: ARITHMETIC SEQUENCES and PARTIAL SUMS (Chapter 9: Discrete Math) 9.11 SECTION 9.2: ARITHMETIC SEQUENCES and PARTIAL SUMS PART A: WHAT IS AN ARITHMETIC SEQUENCE? The following appears to be an example of an arithmetic (stress on the me ) sequence:

More information

Introduction and Preliminaries

Introduction and Preliminaries Chapter 1 Introduction and Preliminaries This chapter serves two purposes. The first purpose is to prepare the readers for the more systematic development in later chapters of methods of real analysis

More information

which has a check digit of 9. This is consistent with the first nine digits of the ISBN, since

which has a check digit of 9. This is consistent with the first nine digits of the ISBN, since vector Then the check digit c is computed using the following procedure: 1. Form the dot product. 2. Divide by 11, thereby producing a remainder c that is an integer between 0 and 10, inclusive. The check

More information

CHEBYSHEV INEQUALITIES AND SELF-DUAL CONES

CHEBYSHEV INEQUALITIES AND SELF-DUAL CONES CHEBYSHEV INEQUALITIES AND SELF-DUAL CONES ZDZISŁAW OTACHEL Dept. of Applied Mathematics and Computer Science University of Life Sciences in Lublin Akademicka 13, 20-950 Lublin, Poland EMail: zdzislaw.otachel@up.lublin.pl

More information

INEQUALITIES FOR THE NORM AND THE NUMERICAL RADIUS OF LINEAR OPERATORS IN HILBERT SPACES

INEQUALITIES FOR THE NORM AND THE NUMERICAL RADIUS OF LINEAR OPERATORS IN HILBERT SPACES INEQUALITIES FOR THE NORM AND THE NUMERICAL RADIUS OF LINEAR OPERATORS IN HILBERT SPACES S.S. DRAGOMIR Abstract. In this paper various inequalities between the operator norm its numerical radius are provided.

More information

Theorem (4.11). Let M be a closed subspace of a Hilbert space H. For any x, y E, the parallelogram law applied to x/2 and y/2 gives.

Theorem (4.11). Let M be a closed subspace of a Hilbert space H. For any x, y E, the parallelogram law applied to x/2 and y/2 gives. Math 641 Lecture #19 4.11, 4.12, 4.13 Inner Products and Linear Functionals (Continued) Theorem (4.10). Every closed, convex set E in a Hilbert space H contains a unique element of smallest norm, i.e.,

More information

Functional Analysis Review

Functional Analysis Review Outline 9.520: Statistical Learning Theory and Applications February 8, 2010 Outline 1 2 3 4 Vector Space Outline A vector space is a set V with binary operations +: V V V and : R V V such that for all

More information

MGM 531 Euclidean Geometry [Geometri Euklidan]

MGM 531 Euclidean Geometry [Geometri Euklidan] UNIVERSITI SINS MLYSI First Semester Examination cademic Session 2015/2016 January 2016 MGM 531 Euclidean Geometry [Geometri Euklidan] Duration : 3 hours [Masa : 3 jam] Please check that this examination

More information

Fixed point theorems of nondecreasing order-ćirić-lipschitz mappings in normed vector spaces without normalities of cones

Fixed point theorems of nondecreasing order-ćirić-lipschitz mappings in normed vector spaces without normalities of cones Available online at www.isr-publications.com/jnsa J. Nonlinear Sci. Appl., 10 (2017), 18 26 Research Article Journal Homepage: www.tjnsa.com - www.isr-publications.com/jnsa Fixed point theorems of nondecreasing

More information

Also, in recent years, Tsallis proposed another entropy measure which in the case of a discrete random variable is given by

Also, in recent years, Tsallis proposed another entropy measure which in the case of a discrete random variable is given by Gibbs-Shannon Entropy and Related Measures: Tsallis Entropy Garimella Rama Murthy, Associate Professor, IIIT---Hyderabad, Gachibowli, HYDERABAD-32, AP, INDIA ABSTRACT In this research paper, it is proved

More information

CHAPTER VIII HILBERT SPACES

CHAPTER VIII HILBERT SPACES CHAPTER VIII HILBERT SPACES DEFINITION Let X and Y be two complex vector spaces. A map T : X Y is called a conjugate-linear transformation if it is a reallinear transformation from X into Y, and if T (λx)

More information

A Note on Singularly Perturbed System

A Note on Singularly Perturbed System Jurnal Matematika dan Sains Vol. 7 No. 1, April 00, hal 7-33 A Note on Singularly Perturbed System Hengki Tasman 1), Theo Tuwankotta ), and Wono Setya Budhi 3) Department of Mathematics, ITB E-mails: 1)

More information

Power Series. Part 1. J. Gonzalez-Zugasti, University of Massachusetts - Lowell

Power Series. Part 1. J. Gonzalez-Zugasti, University of Massachusetts - Lowell Power Series Part 1 1 Power Series Suppose x is a variable and c k & a are constants. A power series about x = 0 is c k x k A power series about x = a is c k x a k a = center of the power series c k =

More information

INDEX. Bolzano-Weierstrass theorem, for sequences, boundary points, bounded functions, 142 bounded sets, 42 43

INDEX. Bolzano-Weierstrass theorem, for sequences, boundary points, bounded functions, 142 bounded sets, 42 43 INDEX Abel s identity, 131 Abel s test, 131 132 Abel s theorem, 463 464 absolute convergence, 113 114 implication of conditional convergence, 114 absolute value, 7 reverse triangle inequality, 9 triangle

More information

Some unified algorithms for finding minimum norm fixed point of nonexpansive semigroups in Hilbert spaces

Some unified algorithms for finding minimum norm fixed point of nonexpansive semigroups in Hilbert spaces An. Şt. Univ. Ovidius Constanţa Vol. 19(1), 211, 331 346 Some unified algorithms for finding minimum norm fixed point of nonexpansive semigroups in Hilbert spaces Yonghong Yao, Yeong-Cheng Liou Abstract

More information

Convergent Iterative Algorithms in the 2-inner Product Space R n

Convergent Iterative Algorithms in the 2-inner Product Space R n Int. J. Open Problems Compt. Math., Vol. 6, No. 4, December 2013 ISSN 1998-6262; Copyright c ICSRS Publication, 2013 www.i-csrs.org Convergent Iterative Algorithms in the 2-inner Product Space R n Iqbal

More information

Final Exam Practice Problems Math 428, Spring 2017

Final Exam Practice Problems Math 428, Spring 2017 Final xam Practice Problems Math 428, Spring 2017 Name: Directions: Throughout, (X,M,µ) is a measure space, unless stated otherwise. Since this is not to be turned in, I highly recommend that you work

More information

3 Orthogonality and Fourier series

3 Orthogonality and Fourier series 3 Orthogonality and Fourier series We now turn to the concept of orthogonality which is a key concept in inner product spaces and Hilbert spaces. We start with some basic definitions. Definition 3.1. Let

More information

ORTHOGONALITY AND LEAST-SQUARES [CHAP. 6]

ORTHOGONALITY AND LEAST-SQUARES [CHAP. 6] ORTHOGONALITY AND LEAST-SQUARES [CHAP. 6] Inner products and Norms Inner product or dot product of 2 vectors u and v in R n : u.v = u 1 v 1 + u 2 v 2 + + u n v n Calculate u.v when u = 1 2 2 0 v = 1 0

More information

A SYNOPSIS OF HILBERT SPACE THEORY

A SYNOPSIS OF HILBERT SPACE THEORY A SYNOPSIS OF HILBERT SPACE THEORY Below is a summary of Hilbert space theory that you find in more detail in any book on functional analysis, like the one Akhiezer and Glazman, the one by Kreiszig or

More information

THE INVERSE FUNCTION THEOREM FOR LIPSCHITZ MAPS

THE INVERSE FUNCTION THEOREM FOR LIPSCHITZ MAPS THE INVERSE FUNCTION THEOREM FOR LIPSCHITZ MAPS RALPH HOWARD DEPARTMENT OF MATHEMATICS UNIVERSITY OF SOUTH CAROLINA COLUMBIA, S.C. 29208, USA HOWARD@MATH.SC.EDU Abstract. This is an edited version of a

More information

EQUIVALENCE OF n-norms ON THE SPACE OF p-summable SEQUENCES

EQUIVALENCE OF n-norms ON THE SPACE OF p-summable SEQUENCES J Indones Math Soc Vol xx, No xx (0xx), xx xx EQUIVALENCE OF n-norms ON THE SPACE OF -SUMMABLE SEQUENCES Anwar Mutaqin 1 and Hendra Gunawan 5 1 Deartment of Mathematics Education, Universitas Sultan Ageng

More information

Data representation and classification

Data representation and classification Representation and classification of data January 25, 2016 Outline Lecture 1: Data Representation 1 Lecture 1: Data Representation Data representation The phrase data representation usually refers to the

More information

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 4 Solutions Please write neatly, and in complete sentences when possible.

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 4 Solutions Please write neatly, and in complete sentences when possible. Math 320: Real Analysis MWF pm, Campion Hall 302 Homework 4 Solutions Please write neatly, and in complete sentences when possible. Do the following problems from the book: 2.6.3, 2.7.4, 2.7.5, 2.7.2,

More information

Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011

Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011 Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011 Section 2.6 (cont.) Properties of Real Functions Here we first study properties of functions from R to R, making use of the additional structure

More information

ANALISIS BIVARIAT DATA NUMERIK DAN NUMERIK Uji Korelasi dan Regresi

ANALISIS BIVARIAT DATA NUMERIK DAN NUMERIK Uji Korelasi dan Regresi ANALISIS BIVARIAT DATA NUMERIK DAN NUMERIK Uji Korelasi dan Regresi Sebagai contoh kita akan melakukan analisis korelasi dan regresi menggunakan data yang sudah dibagikan (ASI Ekslusif) dengan mengambil

More information

4 Hilbert spaces. The proof of the Hilbert basis theorem is not mathematics, it is theology. Camille Jordan

4 Hilbert spaces. The proof of the Hilbert basis theorem is not mathematics, it is theology. Camille Jordan The proof of the Hilbert basis theorem is not mathematics, it is theology. Camille Jordan Wir müssen wissen, wir werden wissen. David Hilbert We now continue to study a special class of Banach spaces,

More information