Walheer Barnabé. Topics in Mathematics Practical Session 2 - Topology & Convex
|
|
- Giles Sanders
- 5 years ago
- Views:
Transcription
1 Topics in Mathematics Practical Session 2 - Topology & Convex Sets
2 Outline (i) Set membership and set operations (ii) Closed and open balls/sets (iii) Points (iv) Sets (v) Convex Sets
3 Set Membership and Set Operations (i) x S indicates that x is an element of S and x S indicates that x is not an element of S. (ii) A B indicates that A is a subset of B. (iii) A B indicates the union of A and B i.e. the elements that belongs to at least one of the sets A and B. (iv) A B indicates the intersection of A and B i.e. the elements that belongs to both A and B. (v) A \ B indicates A minus B i.e. the elements that belongs to A, but not to B.
4 Exercises Give a explicit definition of (ii), (iii), (iv) and (v). Give the definition of a proper subset (A B). Prove that: A = B iff A B and B A. Prove that A A.
5 Closed and open balls/sets B(c, r) = {x R n : d(c, x) < r} is an open ball of R n. B(c, r) = {x R n : d(c, x) r} is a closed ball of R n. (r > 0) A is closed iff all sequences of elements of A that converge, converge in A. B is open iff its complement (B c ) is closed [B c = R n \ B]. An open (closed) ball is a open (closed) set. If A and B are open (closed), then: A B is open (closed). A B is open (closed).
6 Points a is an interior point of A iff a is the center of an open ball in A. Int A = set of all interior points of A. This implies: (i) If a A, then a cannot be an interior point of A. (ii) All points of an open set A are interior points of A. (iii) If all points of A are interior points, then A is open. (iv) The set A is open iff all these points are interior points.
7 Points b is an adherent (or closure) point of B iff there exists a sequence of elements of B that converge through b. Adh B = set of all adherent points of B. Or use: b is an adherent point of B iff all interval centered in b has a non-empty intersection with B. This implies: (i) If b B, then b is an adherent point of B. (ii) The set B is closed iff it contents all these adherent points.
8 Duality: Interior vs Adherent The interior of S is the complement of the set of all adherent points of the complement of S. In this sense Int and Adh are dual notions (kind of involution).
9 Points c is an accumulation (or limit) point of C iff there exists a sequence of elements of C, different of c, that converge through c. Acc C = set of all accumulation points of C. Or use: c is an accumulation point of C iff all interval centered in c has a non-empty intersection with C that is not c. This implies: (i) If c is an acccumulation point of C, then c is an adherent point of C.
10 Exercises: Find Int, Adh and Acc of the following sets. Are the sets open, closed? In R: A = [2, 5] [7, 12], B = {1}, C = ( 1, 3) (0, 2), D = [ 4, 1] {1, 2}, E = R \ [3, 7], F = (, 4] [6, + ) In R 2 : A = R 0 x R, B = (R + ) 2, C = {(x, y) R 2 : 2x + 3y 6, x 0, y 0}, D = {(x, y) R 2 : 0 x 3, 0 y 2} {(3, 3)}, E = {(x, y) R 2 : 1 < x 2 + y 2 < 2} In R 3 : A = (R + 0 )3, B = {(x, y, z) R 3 : 0 x 3, 0 y 2, 0 z 1}, C = {(x, y, z) R 3 : z = x 2 + y 2 }
11 Min, Max, Sup and Inf M is a maximum of A iff M A a A : a M. m is a minimum of A iff m A a A : a m. s is a supremum of A iff a A : a s x R n, a A : x a x s. i is a infimum of A iff a A : a i x R n, a A : x a x i. A is a complete set iff it has an infimum and a supremum.
12 Exercises: Find Min, Max, Sup and Inf of the following sets. A = [0, 1], B = ( 1, 1), C = [ 2, 69), D = R, E = N, F = N 0 Show that sup is unique (using the definition). Derive the relation between inf and min (using the definitions). Is Q complete?
13 Sets A set is bounded iff it is included in a ball. A set is compact iff it is closed and bounded. The neighborhood of a is the set that containts an open ball centered in a. The frontier (or boundary) of A (Fr A or Bd A) is Adh A \ Int A. The exterior of a set is the interior of its complement. The power set of S is the set of all subsets of S (P(S)) 2 n elements.
14 Exercises: Find Fr of the following sets. Are the sets bounded? In R: A = [2, 5] [7, 12], B = {1}, C = ( 1, 3) (0, 2), D = [ 4, 1] {1, 2}, E = R \ [3, 7], F = (, 4] [6, + ) In R 2 : A = R 0 x R, B = (R + ) 2, C = {(x, y) R 2 : 2x + 3y 6, x 0, y 0}, D = {(x, y) R 2 : 0 x 3, 0 y 2} {(3, 3)}, E = {(x, y) R 2 : 1 < x 2 + y 2 < 2} In R 3 : A = (R + 0 )3, B = {(x, y, z) R 3 : 0 x 3, 0 y 2, 0 z 1}, C = {(x, y, z) R 3 : z = x 2 + y 2 }
15 Convex Set A is convex iff x, y A, λ [0, 1], λx + (1 λ)y A. This implies: (i) The line segment passing through two points of A is in A. If A and B are convex, then A B is convex. A B is not convex. V is a cone iff x V, λ R, λx V. A convex hull of W is the smallest convex set that contains W.
16 Exercises: Are the following sets convex? In R: A = [2, 5] [7, 12], B = {1}, C = ( 1, 3) (0, 2), D = [ 4, 1] {1, 2}, E = R \ [3, 7], F = (, 4] [6, + ) In R 2 : A = R 0 x R, B = (R + ) 2, C = {(x, y) R 2 : 2x + 3y 6, x 0, y 0}, D = {(x, y) R 2 : 0 x 3, 0 y 2} {(3, 3)}, E = {(x, y) R 2 : 1 < x 2 + y 2 < 2} In R 3 : A = (R + 0 )3, B = {(x, y, z) R 3 : 0 x 3, 0 y 2, 0 z 1}, C = {(x, y, z) R 3 : z = x 2 + y 2 }
However, this is not always true! For example, this fails if both A and B are closed and unbounded (find an example).
98 CHAPTER 3. PROPERTIES OF CONVEX SETS: A GLIMPSE 3.2 Separation Theorems It seems intuitively rather obvious that if A and B are two nonempty disjoint convex sets in A 2, then there is a line, H, separating
More informationChapter 11. Topological Spaces: General Properties
11.1. Open Sets, Closed Sets, Bases, and Subbases 1 Chapter 11. Topological Spaces: General Properties Section 11.1. Open Sets, Closed Sets, Bases, and Subbases Note. In this section, we define a topological
More informationIn class 75min: 2:55-4:10 Thu 9/30.
MATH 4530 Topology. In class 75min: 2:55-4:10 Thu 9/30. Prelim I Solutions Problem 1: Consider the following topological spaces: (1) Z as a subspace of R with the finite complement topology (2) [0, π]
More informationCompact Sets. James K. Peterson. September 15, Department of Biological Sciences and Department of Mathematical Sciences Clemson University
Compact Sets James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 15, 2017 Outline 1 Closed Sets 2 Compactness 3 Homework Closed Sets
More informationTopological properties of convex sets
Division of the Humanities and Social Sciences Ec 181 KC Border Convex Analysis and Economic Theory Winter 2018 Topic 5: Topological properties of convex sets 5.1 Interior and closure of convex sets Let
More informationLecture 2. Topology of Sets in R n. August 27, 2008
Lecture 2 Topology of Sets in R n August 27, 2008 Outline Vectors, Matrices, Norms, Convergence Open and Closed Sets Special Sets: Subspace, Affine Set, Cone, Convex Set Special Convex Sets: Hyperplane,
More informationREVIEW OF FUZZY SETS
REVIEW OF FUZZY SETS CONNER HANSEN 1. Introduction L. A. Zadeh s paper Fuzzy Sets* [1] introduces the concept of a fuzzy set, provides definitions for various fuzzy set operations, and proves several properties
More informationOpen and Closed Sets
Open and Closed Sets Definition: A subset S of a metric space (X, d) is open if it contains an open ball about each of its points i.e., if x S : ɛ > 0 : B(x, ɛ) S. (1) Theorem: (O1) and X are open sets.
More informationAn introduction to Topological Data Analysis through persistent homology: Intro and geometric inference
Sophia-Antipolis, January 2016 Winter School An introduction to Topological Data Analysis through persistent homology: Intro and geometric inference Frédéric Chazal INRIA Saclay - Ile-de-France frederic.chazal@inria.fr
More informationNumerical Optimization
Convex Sets Computer Science and Automation Indian Institute of Science Bangalore 560 012, India. NPTEL Course on Let x 1, x 2 R n, x 1 x 2. Line and line segment Line passing through x 1 and x 2 : {y
More informationFACES OF CONVEX SETS
FACES OF CONVEX SETS VERA ROSHCHINA Abstract. We remind the basic definitions of faces of convex sets and their basic properties. For more details see the classic references [1, 2] and [4] for polytopes.
More informationOn Soft Topological Linear Spaces
Republic of Iraq Ministry of Higher Education and Scientific Research University of AL-Qadisiyah College of Computer Science and Formation Technology Department of Mathematics On Soft Topological Linear
More informationConvexity: an introduction
Convexity: an introduction Geir Dahl CMA, Dept. of Mathematics and Dept. of Informatics University of Oslo 1 / 74 1. Introduction 1. Introduction what is convexity where does it arise main concepts and
More informationBounded subsets of topological vector spaces
Chapter 2 Bounded subsets of topological vector spaces In this chapter we will study the notion of bounded set in any t.v.s. and analyzing some properties which will be useful in the following and especially
More informationTopology problem set Integration workshop 2010
Topology problem set Integration workshop 2010 July 28, 2010 1 Topological spaces and Continuous functions 1.1 If T 1 and T 2 are two topologies on X, show that (X, T 1 T 2 ) is also a topological space.
More informationTopology 550A Homework 3, Week 3 (Corrections: February 22, 2012)
Topology 550A Homework 3, Week 3 (Corrections: February 22, 2012) Michael Tagare De Guzman January 31, 2012 4A. The Sorgenfrey Line The following material concerns the Sorgenfrey line, E, introduced in
More informationIntroduction to optimization
Introduction to optimization G. Ferrari Trecate Dipartimento di Ingegneria Industriale e dell Informazione Università degli Studi di Pavia Industrial Automation Ferrari Trecate (DIS) Optimization Industrial
More informationLocally convex topological vector spaces
Chapter 4 Locally convex topological vector spaces 4.1 Definition by neighbourhoods Let us start this section by briefly recalling some basic properties of convex subsets of a vector space over K (where
More informationSets. De Morgan s laws. Mappings. Definition. Definition
Sets Let X and Y be two sets. Then the set A set is a collection of elements. Two sets are equal if they contain exactly the same elements. A is a subset of B (A B) if all the elements of A also belong
More informationGenerell Topologi. Richard Williamson. May 27, 2013
Generell Topologi Richard Williamson May 27, 2013 1 1 Tuesday 15th January 1.1 Topological spaces definition, terminology, finite examples Definition 1.1. A topological space is a pair (X, O) of a set
More informationMath 395: Topology. Bret Benesh (College of Saint Benedict/Saint John s University)
Math 395: Topology Bret Benesh (College of Saint Benedict/Saint John s University) October 30, 2012 ii Contents Acknowledgments v 1 Topological Spaces 1 2 Closed sets and Hausdorff spaces 7 iii iv CONTENTS
More informationDivision of the Humanities and Social Sciences. Convex Analysis and Economic Theory Winter Separation theorems
Division of the Humanities and Social Sciences Ec 181 KC Border Convex Analysis and Economic Theory Winter 2018 Topic 8: Separation theorems 8.1 Hyperplanes and half spaces Recall that a hyperplane in
More informationEC 521 MATHEMATICAL METHODS FOR ECONOMICS. Lecture 2: Convex Sets
EC 51 MATHEMATICAL METHODS FOR ECONOMICS Lecture : Convex Sets Murat YILMAZ Boğaziçi University In this section, we focus on convex sets, separating hyperplane theorems and Farkas Lemma. And as an application
More informationTHREE LECTURES ON BASIC TOPOLOGY. 1. Basic notions.
THREE LECTURES ON BASIC TOPOLOGY PHILIP FOTH 1. Basic notions. Let X be a set. To make a topological space out of X, one must specify a collection T of subsets of X, which are said to be open subsets of
More informationLecture 15: The subspace topology, Closed sets
Lecture 15: The subspace topology, Closed sets 1 The Subspace Topology Definition 1.1. Let (X, T) be a topological space with topology T. subset of X, the collection If Y is a T Y = {Y U U T} is a topology
More informationMath 5593 Linear Programming Lecture Notes
Math 5593 Linear Programming Lecture Notes Unit II: Theory & Foundations (Convex Analysis) University of Colorado Denver, Fall 2013 Topics 1 Convex Sets 1 1.1 Basic Properties (Luenberger-Ye Appendix B.1).........................
More informationTopology I Test 1 Solutions October 13, 2008
Topology I Test 1 Solutions October 13, 2008 1. Do FIVE of the following: (a) Give a careful definition of connected. A topological space X is connected if for any two sets A and B such that A B = X, we
More informationLecture 2 September 3
EE 381V: Large Scale Optimization Fall 2012 Lecture 2 September 3 Lecturer: Caramanis & Sanghavi Scribe: Hongbo Si, Qiaoyang Ye 2.1 Overview of the last Lecture The focus of the last lecture was to give
More informationCMU-Q Lecture 9: Optimization II: Constrained,Unconstrained Optimization Convex optimization. Teacher: Gianni A. Di Caro
CMU-Q 15-381 Lecture 9: Optimization II: Constrained,Unconstrained Optimization Convex optimization Teacher: Gianni A. Di Caro GLOBAL FUNCTION OPTIMIZATION Find the global maximum of the function f x (and
More informationON DECOMPOSITION OF FUZZY BԐ OPEN SETS
ON DECOMPOSITION OF FUZZY BԐ OPEN SETS 1 B. Amudhambigai, 2 K. Saranya 1,2 Department of Mathematics, Sri Sarada College for Women, Salem-636016, Tamilnadu,India email: 1 rbamudha@yahoo.co.in, 2 saranyamath88@gmail.com
More informationShiqian Ma, MAT-258A: Numerical Optimization 1. Chapter 2. Convex Optimization
Shiqian Ma, MAT-258A: Numerical Optimization 1 Chapter 2 Convex Optimization Shiqian Ma, MAT-258A: Numerical Optimization 2 2.1. Convex Optimization General optimization problem: min f 0 (x) s.t., f i
More informationMathematical Morphology and Distance Transforms. Robin Strand
Mathematical Morphology and Distance Transforms Robin Strand robin.strand@it.uu.se Morphology Form and structure Mathematical framework used for: Pre-processing Noise filtering, shape simplification,...
More informationHomework Set #2 Math 440 Topology Topology by J. Munkres
Homework Set #2 Math 440 Topology Topology by J. Munkres Clayton J. Lungstrum October 26, 2012 Exercise 1. Prove that a topological space X is Hausdorff if and only if the diagonal = {(x, x) : x X} is
More informationLecture 1: Introduction
Lecture 1 1 Linear and Combinatorial Optimization Anders Heyden Centre for Mathematical Sciences Lecture 1: Introduction The course and its goals Basic concepts Optimization Combinatorial optimization
More information2.8. Connectedness A topological space X is said to be disconnected if X is the disjoint union of two non-empty open subsets. The space X is said to
2.8. Connectedness A topological space X is said to be disconnected if X is the disjoint union of two non-empty open subsets. The space X is said to be connected if it is not disconnected. A subset of
More informationConvexity and Optimization
Convexity and Optimization Richard Lusby Department of Management Engineering Technical University of Denmark Today s Material Extrema Convex Function Convex Sets Other Convexity Concepts Unconstrained
More informationSection 17. Closed Sets and Limit Points
17. Closed Sets and Limit Points 1 Section 17. Closed Sets and Limit Points Note. In this section, we finally define a closed set. We also introduce several traditional topological concepts, such as limit
More informationM3P1/M4P1 (2005) Dr M Ruzhansky Metric and Topological Spaces Summary of the course: definitions, examples, statements.
M3P1/M4P1 (2005) Dr M Ruzhansky Metric and Topological Spaces Summary of the course: definitions, examples, statements. Chapter 1: Metric spaces and convergence. (1.1) Recall the standard distance function
More informationL. A. Zadeh: Fuzzy Sets. (1965) A review
POSSIBILISTIC INFORMATION: A Tutorial L. A. Zadeh: Fuzzy Sets. (1965) A review George J. Klir Petr Osička State University of New York (SUNY) Binghamton, New York 13902, USA gklir@binghamton.edu Palacky
More information4 Basis, Subbasis, Subspace
4 Basis, Subbasis, Subspace Our main goal in this chapter is to develop some tools that make it easier to construct examples of topological spaces. By Definition 3.12 in order to define a topology on a
More informationOPERATIONS RESEARCH. Linear Programming Problem
OPERATIONS RESEARCH Chapter 1 Linear Programming Problem Prof. Bibhas C. Giri Department of Mathematics Jadavpur University Kolkata, India Email: bcgiri.jumath@gmail.com 1.0 Introduction Linear programming
More informationLecture 5: Duality Theory
Lecture 5: Duality Theory Rajat Mittal IIT Kanpur The objective of this lecture note will be to learn duality theory of linear programming. We are planning to answer following questions. What are hyperplane
More informationMathematical Programming and Research Methods (Part II)
Mathematical Programming and Research Methods (Part II) 4. Convexity and Optimization Massimiliano Pontil (based on previous lecture by Andreas Argyriou) 1 Today s Plan Convex sets and functions Types
More informationNotes on Topology. Andrew Forrester January 28, Notation 1. 2 The Big Picture 1
Notes on Topology Andrew Forrester January 28, 2009 Contents 1 Notation 1 2 The Big Picture 1 3 Fundamental Concepts 2 4 Topological Spaces and Topologies 2 4.1 Topological Spaces.........................................
More informationPolar Duality and Farkas Lemma
Lecture 3 Polar Duality and Farkas Lemma October 8th, 2004 Lecturer: Kamal Jain Notes: Daniel Lowd 3.1 Polytope = bounded polyhedron Last lecture, we were attempting to prove the Minkowsky-Weyl Theorem:
More informationMorphological Image Processing
Morphological Image Processing Morphology Identification, analysis, and description of the structure of the smallest unit of words Theory and technique for the analysis and processing of geometric structures
More informationInternational Journal of Scientific & Engineering Research, Volume 7, Issue 2, February ISSN
International Journal of Scientific & Engineering Research, Volume 7, Issue 2, February-2016 149 KEY PROPERTIES OF HESITANT FUZZY SOFT TOPOLOGICAL SPACES ASREEDEVI, DRNRAVI SHANKAR Abstract In this paper,
More informationLecture 5: Simplicial Complex
Lecture 5: Simplicial Complex 2-Manifolds, Simplex and Simplicial Complex Scribed by: Lei Wang First part of this lecture finishes 2-Manifolds. Rest part of this lecture talks about simplicial complex.
More informationLecture-12: Closed Sets
and Its Examples Properties of Lecture-12: Dr. Department of Mathematics Lovely Professional University Punjab, India October 18, 2014 Outline Introduction and Its Examples Properties of 1 Introduction
More informationCS522: Advanced Algorithms
Lecture 1 CS5: Advanced Algorithms October 4, 004 Lecturer: Kamal Jain Notes: Chris Re 1.1 Plan for the week Figure 1.1: Plan for the week The underlined tools, weak duality theorem and complimentary slackness,
More informationConvexity and Optimization
Convexity and Optimization Richard Lusby DTU Management Engineering Class Exercises From Last Time 2 DTU Management Engineering 42111: Static and Dynamic Optimization (3) 18/09/2017 Today s Material Extrema
More informationA Little Point Set Topology
A Little Point Set Topology A topological space is a generalization of a metric space that allows one to talk about limits, convergence, continuity and so on without requiring the concept of a distance
More informationElementary Topology. Note: This problem list was written primarily by Phil Bowers and John Bryant. It has been edited by a few others along the way.
Elementary Topology Note: This problem list was written primarily by Phil Bowers and John Bryant. It has been edited by a few others along the way. Definition. properties: (i) T and X T, A topology on
More informationTopology notes. Basic Definitions and Properties.
Topology notes. Basic Definitions and Properties. Intuitively, a topological space consists of a set of points and a collection of special sets called open sets that provide information on how these points
More informationConvex Sets. Pontus Giselsson
Convex Sets Pontus Giselsson 1 Today s lecture convex sets convex, affine, conical hulls closure, interior, relative interior, boundary, relative boundary separating and supporting hyperplane theorems
More informationPartition of a Nonempty Fuzzy Set in Nonempty Convex Fuzzy Subsets
Applied Mathematical Sciences, Vol. 6, 2012, no. 59, 2917-2921 Partition of a Nonempty Fuzzy Set in Nonempty Convex Fuzzy Subsets Omar Salazar Morales Universidad Distrital Francisco José de Caldas, Bogotá,
More informationOptimality certificates for convex minimization and Helly numbers
Optimality certificates for convex minimization and Helly numbers Amitabh Basu Michele Conforti Gérard Cornuéjols Robert Weismantel Stefan Weltge October 20, 2016 Abstract We consider the problem of minimizing
More informationEpimorphisms in the Category of Hausdorff Fuzzy Topological Spaces
Annals of Pure and Applied Mathematics Vol. 7, No. 1, 2014, 35-40 ISSN: 2279-087X (P), 2279-0888(online) Published on 9 September 2014 www.researchmathsci.org Annals of Epimorphisms in the Category of
More informationOther Voronoi/Delaunay Structures
Other Voronoi/Delaunay Structures Overview Alpha hulls (a subset of Delaunay graph) Extension of Voronoi Diagrams Convex Hull What is it good for? The bounding region of a point set Not so good for describing
More informationTOPOLOGY CHECKLIST - SPRING 2010
TOPOLOGY CHECKLIST - SPRING 2010 The list below serves as an indication of what we have covered in our course on topology. (It was written in a hurry, so there is a high risk of some mistake being made
More informationA mathematician s view on Three gives birth to innumerable things
A mathematician s view on Three gives birth to innumerable things Qinghai Zhang Department of Mathematics, University of Utah, 155 S. 1400 E., Rm 233, Salt Lake City UT 84103 Abstract Philosophy underlies
More informationLecture 2 Convex Sets
Optimization Theory and Applications Lecture 2 Convex Sets Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Fall 2016 2016/9/29 Lecture 2: Convex Sets 1 Outline
More informationMath 528 Jan 11, Geometry and Topology II Fall 2005, USC
Math 528 Jan 11, 2005 1 Geometry and Topology II Fall 2005, USC Lecture Notes 2 1.4 Definition of Manifolds By a basis for a topological space (X, T), we mean a subset B of T such that for any U T and
More informationJohns Hopkins Math Tournament Proof Round: Point Set Topology
Johns Hopkins Math Tournament 2019 Proof Round: Point Set Topology February 9, 2019 Problem Points Score 1 3 2 6 3 6 4 6 5 10 6 6 7 8 8 6 9 8 10 8 11 9 12 10 13 14 Total 100 Instructions The exam is worth
More informationPoint-Set Topology 1. TOPOLOGICAL SPACES AND CONTINUOUS FUNCTIONS
Point-Set Topology 1. TOPOLOGICAL SPACES AND CONTINUOUS FUNCTIONS Definition 1.1. Let X be a set and T a subset of the power set P(X) of X. Then T is a topology on X if and only if all of the following
More informationOptimality certificates for convex minimization and Helly numbers
Optimality certificates for convex minimization and Helly numbers Amitabh Basu Michele Conforti Gérard Cornuéjols Robert Weismantel Stefan Weltge May 10, 2017 Abstract We consider the problem of minimizing
More informationTaibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103. Chapter 2. Sets
Taibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103 Chapter 2 Sets Slides are adopted from Discrete Mathematics and It's Applications Kenneth H.
More informationLecture 4: Convexity
10-725: Convex Optimization Fall 2013 Lecture 4: Convexity Lecturer: Barnabás Póczos Scribes: Jessica Chemali, David Fouhey, Yuxiong Wang Note: LaTeX template courtesy of UC Berkeley EECS dept. Disclaimer:
More informationTopology - I. Michael Shulman WOMP 2004
Topology - I Michael Shulman WOMP 2004 1 Topological Spaces There are many different ways to define a topological space; the most common one is as follows: Definition 1.1 A topological space (often just
More informationSimplex Algorithm in 1 Slide
Administrivia 1 Canonical form: Simplex Algorithm in 1 Slide If we do pivot in A r,s >0, where c s
More informationLecture - 8A: Subbasis of Topology
Lecture - 8A: Dr. Department of Mathematics Lovely Professional University Punjab, India October 18, 2014 Outline 1 Introduction 2 3 4 Introduction I As we know that topology generated by a basis B may
More informationModeling and Analysis of Hybrid Systems
Modeling and Analysis of Hybrid Systems Convex polyhedra Prof. Dr. Erika Ábrahám Informatik 2 - LuFG Theory of Hybrid Systems RWTH Aachen University Szeged, Hungary, 27 September - 06 October 2017 Ábrahám
More informationModeling and Analysis of Hybrid Systems
Modeling and Analysis of Hybrid Systems 6. Convex polyhedra Prof. Dr. Erika Ábrahám Informatik 2 - LuFG Theory of Hybrid Systems RWTH Aachen University Szeged, Hungary, 27 September - 06 October 2017 Ábrahám
More informationIntroduction to Algebraic and Geometric Topology Week 5
Introduction to Algebraic and Geometric Topology Week 5 Domingo Toledo University of Utah Fall 2017 Topology of Metric Spaces I (X, d) metric space. I Recall the definition of Open sets: Definition U
More informationA Note on Fuzzy Boundary of Fuzzy Bitopological Spaces on the Basis of Reference Function
Advances in Fuzzy Mathematics. ISSN 0973-533X Volume 12, Number 3 (2017), pp. 639-644 Research India Publications http://www.ripublication.com A Note on Fuzzy Boundary of Fuzzy Bitopological Spaces on
More informationConvex Sets (cont.) Convex Functions
Convex Sets (cont.) Convex Functions Optimization - 10725 Carlos Guestrin Carnegie Mellon University February 27 th, 2008 1 Definitions of convex sets Convex v. Non-convex sets Line segment definition:
More information[Ch 6] Set Theory. 1. Basic Concepts and Definitions. 400 lecture note #4. 1) Basics
400 lecture note #4 [Ch 6] Set Theory 1. Basic Concepts and Definitions 1) Basics Element: ; A is a set consisting of elements x which is in a/another set S such that P(x) is true. Empty set: notated {
More informationLecture 2 - Introduction to Polytopes
Lecture 2 - Introduction to Polytopes Optimization and Approximation - ENS M1 Nicolas Bousquet 1 Reminder of Linear Algebra definitions Let x 1,..., x m be points in R n and λ 1,..., λ m be real numbers.
More informationBasics of Combinatorial Topology
Chapter 7 Basics of Combinatorial Topology 7.1 Simplicial and Polyhedral Complexes In order to study and manipulate complex shapes it is convenient to discretize these shapes and to view them as the union
More informationPOINT SET TOPOLOGY. Introduction
POINT SET TOPOLOGY Introduction In order to establish a foundation for topological evolution, an introduction to topological ideas and definitions is presented in terms of point set methods for which the
More information60 2 Convex sets. {x a T x b} {x ã T x b}
60 2 Convex sets Exercises Definition of convexity 21 Let C R n be a convex set, with x 1,, x k C, and let θ 1,, θ k R satisfy θ i 0, θ 1 + + θ k = 1 Show that θ 1x 1 + + θ k x k C (The definition of convexity
More informationPOLYHEDRAL GEOMETRY. Convex functions and sets. Mathematical Programming Niels Lauritzen Recall that a subset C R n is convex if
POLYHEDRAL GEOMETRY Mathematical Programming Niels Lauritzen 7.9.2007 Convex functions and sets Recall that a subset C R n is convex if {λx + (1 λ)y 0 λ 1} C for every x, y C and 0 λ 1. A function f :
More informationTopology Homework 3. Section Section 3.3. Samuel Otten
Topology Homework 3 Section 3.1 - Section 3.3 Samuel Otten 3.1 (1) Proposition. The intersection of finitely many open sets is open and the union of finitely many closed sets is closed. Proof. Note that
More informationRigidity of ball-polyhedra via truncated Voronoi and Delaunay complexes
!000111! NNNiiinnnttthhh IIInnnttteeerrrnnnaaatttiiiooonnnaaalll SSSyyymmmpppooosssiiiuuummm ooonnn VVVooorrrooonnnoooiii DDDiiiaaagggrrraaammmsss iiinnn SSSccciiieeennnccceee aaannnddd EEEnnngggiiinnneeeeeerrriiinnnggg
More information= [ U 1 \ U 2 = B \ [ B \ B.
5. Mon, Sept. 8 At the end of class on Friday, we introduced the notion of a topology, and I asked you to think about how many possible topologies there are on a 3-element set. The answer is... 29. The
More informationOn Fuzzy Topological Spaces Involving Boolean Algebraic Structures
Journal of mathematics and computer Science 15 (2015) 252-260 On Fuzzy Topological Spaces Involving Boolean Algebraic Structures P.K. Sharma Post Graduate Department of Mathematics, D.A.V. College, Jalandhar
More informationEc 181: Convex Analysis and Economic Theory
Division of the Humanities and Social Sciences Ec 181: Convex Analysis and Economic Theory KC Border Winter 2018 v. 2018.03.08::13.11 src: front KC Border: for Ec 181, Winter 2018 Woe to the author who
More informationMorphological Image Processing
Morphological Image Processing Binary image processing In binary images, we conventionally take background as black (0) and foreground objects as white (1 or 255) Morphology Figure 4.1 objects on a conveyor
More informationSubmodularity Reading Group. Matroid Polytopes, Polymatroid. M. Pawan Kumar
Submodularity Reading Group Matroid Polytopes, Polymatroid M. Pawan Kumar http://www.robots.ox.ac.uk/~oval/ Outline Linear Programming Matroid Polytopes Polymatroid Polyhedron Ax b A : m x n matrix b:
More informationLectures on Order and Topology
Lectures on Order and Topology Antonino Salibra 17 November 2014 1 Topology: main definitions and notation Definition 1.1 A topological space X is a pair X = ( X, OX) where X is a nonempty set and OX is
More information2. Convex sets. x 1. x 2. affine set: contains the line through any two distinct points in the set
2. Convex sets Convex Optimization Boyd & Vandenberghe affine and convex sets some important examples operations that preserve convexity generalized inequalities separating and supporting hyperplanes dual
More informationLinear Programming. Larry Blume. Cornell University & The Santa Fe Institute & IHS
Linear Programming Larry Blume Cornell University & The Santa Fe Institute & IHS Linear Programs The general linear program is a constrained optimization problem where objectives and constraints are all
More informationLinear programming and duality theory
Linear programming and duality theory Complements of Operations Research Giovanni Righini Linear Programming (LP) A linear program is defined by linear constraints, a linear objective function. Its variables
More informationConic Duality. yyye
Conic Linear Optimization and Appl. MS&E314 Lecture Note #02 1 Conic Duality Yinyu Ye Department of Management Science and Engineering Stanford University Stanford, CA 94305, U.S.A. http://www.stanford.edu/
More informationPart IV. 2D Clipping
Part IV 2D Clipping The Liang-Barsky algorithm Boolean operations on polygons Outline The Liang-Barsky algorithm Boolean operations on polygons Clipping The goal of clipping is mainly to eliminate parts
More informationINTRODUCTION Joymon Joseph P. Neighbours in the lattice of topologies Thesis. Department of Mathematics, University of Calicut, 2003
INTRODUCTION Joymon Joseph P. Neighbours in the lattice of topologies Thesis. Department of Mathematics, University of Calicut, 2003 INTRODUCTION The collection C(X) of all topologies on a fixed non-empty
More informationConvex Optimization. Convex Sets. ENSAE: Optimisation 1/24
Convex Optimization Convex Sets ENSAE: Optimisation 1/24 Today affine and convex sets some important examples operations that preserve convexity generalized inequalities separating and supporting hyperplanes
More informationLecture : Topological Space
Example of Lecture : Dr. Department of Mathematics Lovely Professional University Punjab, India October 18, 2014 Outline Example of 1 2 3 Example of 4 5 6 Example of I Topological spaces and continuous
More informationLecture 1 Discrete Geometric Structures
Lecture 1 Discrete Geometric Structures Jean-Daniel Boissonnat Winter School on Computational Geometry and Topology University of Nice Sophia Antipolis January 23-27, 2017 Computational Geometry and Topology
More informationMetric and metrizable spaces
Metric and metrizable spaces These notes discuss the same topic as Sections 20 and 2 of Munkres book; some notions (Symmetric, -metric, Ψ-spaces...) are not discussed in Munkres book.. Symmetric, -metric,
More information