TA: Jade Cheng ICS 241 Recitation Lecture Note #5 September 25, Let be the following relation defined on the set,,, :,,,,,,,,,,,,,,,,,,,,,.
|
|
- Stewart Richard
- 6 years ago
- Views:
Transcription
1 TA: Jade Cheng ICS 241 Recitation Lecture Note #5 September 25, 2009 Recitation #5 Let be the following relation defined on the set,,, :,,,,,,,,,,,,,,,,,,,,,. Determine whether is [Chapter 8.1 Review] a. Reflexive is reflexive because contains,,,,,, and,. b. symmetric is not symmetric because,, but,. c. antisymmetric is not antisymmetric because,, and,,.but. d. transitive is not transitive because, for example,, and,, but,. Let be the following relation on the set of real numbers: Determine whether is [Chapter 8.1 Review] a. Reflexive, where is the loor of. is reflexive because is true from all real numbers.
2 b. symmetric is symmetric suppose ; then. c. antisymmetric is not antisymmetric: we can have and for distinct and. For example, d. transitive is transitive, suppose and ; from transitivity of equality of real numbers, it follows that. Answer the following questions regarding this Flight Table: [Chapter 8.2 Review] Airline Flight_number Gate Destination Departure_time N Detroit 08:10 A Denver 08:17 A Anchorage 08:22 A Honolulu 08:30 N Detroit 08:47 A Denver 09:10 N Detroit 09:44 a. Assuming that no new -tuples are added, find a composite key with two fields containing the Airline field for the database in the Flight Table. Airline and Flight_number; Airline and Departure_time b. What do you obtain when you apply the selection operator, where is the condition Destination = Detroit, to the data base in the Flight Table. (N, 122, 34, Detroit, 08:10), (N, 199, 13, Detroit, 08:47), (N, 322, 34, Detroit, 09:44). c. What do you obtain when you apply the selection operator, where is the condition (Airline = N) (Destination = Denver), to the data base in the Flight Table. (N, 122, 34, Detroit, 08:10), (N, 199, 13, Detroit, 08:47), (N, 322, 34, Detroit, 09:44), (A, 221, 22, Denver, 08:17), (A, 222, 22, Denver, 09:10).
3 d. Display the table produced by applying the projection, to the Flight Table. Airline Destination N Detroit A Denver A Anchorage A Honolulu N Detroit A Denver N Detroit Show that if and are conditions that elements of the -ary relation may satisfy, then. [Chapter 8.2 Review] Both sides of this equation pick out the subset of consisting of those -tuples satisfying both conditions and.,,. Give an example to show that if and are both -ary relations, then,, may be different from,,,,. [Chapter 8.2 Review] Let set be the -tuple relation below: Airline Flight_number Gate Destination Departure_time N Detroit 08:10 A Denver 08:17 A Anchorage 08:22 A Honolulu 08:30 Let set be the -tuple relation below: Airline Flight_number Gate Destination Departure_time A Denver 08:17 A Anchorage 08:22 A Honolulu 08:30 N Detroit 08:47 A Denver 09:10 N Detroit 09:44
4 By definition contains the set elements that are in but not in. So is as below: Airline Flight_number Gate Destination Departure_time N Detroit 08:10 Let 1, We obtain the following relationship regarding,, and,,,, :,, N.,,,, N, A N, A. N,,,,,,. Represent each of these relations on 1, 2, 3 with a matrix (with the elements of this set listed in increasing order) [Chapter 8.3 Review] a. 1, 1, 1, 2, 1, b. 1, 2, 2, 1, 2, 2, 3, c. 1, 1, 1, 2, 1, 3, 2, 2, 2, 3, 3,
5 List the ordered pairs in the relations on 1, 2, 3 corresponding to these matrices (where the rows and columns correspond to the integers listed in increasing order). [Chapter 8.3 Review] a , 1, 1, 3, 2, 2, 3, 1, 3, 3. b. 1, 2, 2, 2, 3, 2. c , 1, 2, 2, 1, 3 2, 1 2, 3 3, 1 3, 2 3, 3. Determine whether the relations represented by the matrices in the previous Question are reflexive, irreflexive, symmetric, antisymmetric. [Chapter 8.3 Review] The matrix representing a reflexive relation has 1 s for all its main diagonal entries such as: 1??? 1?.?? 1 The matrix representing a irreflexive relation has 0 s for all its main diagonal entries such as 0??? 0?.?? 0 The matrix representing a symmetric relation has a symmetric 1 s and 0 s layout according to its main diagonal, such as?? 0?? ? The matrix representing an antisymmetric relation has all 1 s having 0 s as the counterpart according to its main diagonal, such as? 1 0 0? ?
6 1 0 1 So it s clear is reflexive, and symmetric, is antisymmetric, is symmetric. Let be the relation represented by the matrix: [Chapter 8.3 Review] Find the matrices that represent,, and Some Problems that appeared in HW#2 and E1 Find the number of solutions of the equation 17, where, 1, 2, 3, 4, are nonnegative integers such that 3, 4, 5, and 8. [Chapter 7.6 Review] To apply the principle of inclusion-exclusion, let a solution have property if 3, property if 4, property if 5, and property if 8. The number of solutions satisfying the inequalities 3, 4, 5 and 8 is
7 . total number of solutions , number of solutions with , total number of solutions , total number of solutions , total number of solutions , total number of solutions 3 and , total number of solutions 3 and , total number of solutions 3 and , 4 35 total number of solutions 4 and , 6 84 total number of solutions 4 and , 3 20 total number of solutions 5 and , 2 10 total number of solutions 3, 4, , 2 10 total number of solutions 3, 4, 8 0 total number of solutions 3, 5, 8 0 total number of solutions 4, 5, 8 0 total number of solutions 3, 4, 5, 8 0 Inserting these quantities into the formula for shows that the number of solutions with that 3, 4, 5, and 8 equals: Determine which of these are linear homogeneous recurrence relations with constant coefficients. Also, find the degree of those that are. [Chapter 7.2] a. 3 Linear, homogeneous, with constant coefficients, degree 2. b. 3 Linear, with constant coefficients but not homogeneous.
8 c. not Linear. d. 2 Linear, homogeneous, with constant coefficients, degree 3. e. / Linear, homogeneous, but not with constant coefficients. f. 3 Linear, with constant coefficients, but not homogeneous. g Linear, homogeneous, with constant coefficients, degree 7. Solve the recurrence relation 2 2 with initial condition 4. [Chapter 7.2 Review] The characteristic equation for the associated homogeneous recurrence relation is 2 0. So it has solutions 2 Therefore the general solution to the associated homogeneous recurrence relation is: 2. To obtain a particular solution to the given recurrence relation, try obtaining:,
9 The coefficient of, terms and the constant term must each equal 0. Therefore, we have Hence, we have 2 8 and 12. Therefore: The initial condition 4, yields the system of equations coefficient: The coefficient is found to be 13. Therefore the solution to the given recurrence relation is:
Department of Computer Science University at Albany, State University of New York Solutions to Sample Discrete Mathematics Examination I (Spring 2008)
Department of Computer Science University at Albany, State University of New York Solutions to Sample Discrete Mathematics Examination I (Spring 2008) Problem 1: Suppose A, B, C and D are arbitrary sets.
More informationRelationships between elements of sets occur in many contexts. Every day we deal with
C H A P T E R 9 Relations 9.1 Relations and Their Properties 9.2 n-ary Relations and Their Applications 9.3 Representing Relations 9.4 Closures of Relations 9.5 Equivalence Relations 9.6 Partial Orderings
More informationMath 3000 Section 003 Intro to Abstract Math Final Exam
Math 3000 Section 003 Intro to Abstract Math Final Exam Department of Mathematical and Statistical Sciences University of Colorado Denver, Spring 2012 Name: Problem 1a-j 2 3a-b 4a-b 5a-c 6a-c 7a-b 8a-j
More informationProblem 1: Suppose A, B, C and D are finite sets such that A B = C D and C = D. Prove or disprove: A = B.
Department of Computer Science University at Albany, State University of New York Solutions to Sample Discrete Mathematics Examination III (Spring 2007) Problem 1: Suppose A, B, C and D are finite sets
More information22A-2 SUMMER 2014 LECTURE Agenda
22A-2 SUMMER 204 LECTURE 2 NATHANIEL GALLUP The Dot Product Continued Matrices Group Work Vectors and Linear Equations Agenda 2 Dot Product Continued Angles between vectors Given two 2-dimensional vectors
More informationMath.3336: Discrete Mathematics. Chapter 9 Relations
Math.3336: Discrete Mathematics Chapter 9 Relations Instructor: Dr. Blerina Xhabli Department of Mathematics, University of Houston https://www.math.uh.edu/ blerina Email: blerina@math.uh.edu Fall 2018
More informationCSC Discrete Math I, Spring Relations
CSC 125 - Discrete Math I, Spring 2017 Relations Binary Relations Definition: A binary relation R from a set A to a set B is a subset of A B Note that a relation is more general than a function Example:
More informationRelations. Relations of Sets N-ary Relations Relational Databases Binary Relation Properties Equivalence Relations. Reading (Epp s textbook)
Relations Relations of Sets N-ary Relations Relational Databases Binary Relation Properties Equivalence Relations Reading (Epp s textbook) 8.-8.3. Cartesian Products The symbol (a, b) denotes the ordered
More informationDefinition 2.3. We define addition and multiplication of matrices as follows.
14 Chapter 2 Matrices In this chapter, we review matrix algebra from Linear Algebra I, consider row and column operations on matrices, and define the rank of a matrix. Along the way prove that the row
More informationDiscrete Structures: Sample Questions, Exam 2, SOLUTIONS
Discrete Structures: Sample Questions, Exam 2, SOLUTIONS (This is longer than the actual test.) 1. Show that any postage of 8 cents or more can be achieved by using only -cent and 5-cent stamps. We proceed
More informationCHAPTER 1. Relations. 1. Relations and Their Properties. Discussion
CHAPTER 1 Relations 1. Relations and Their Properties 1.1. Definition of a Relation. Definition 1.1.1. A binary relation from a set A to a set B is a subset R A B. If (a, b) R we say a is Related to b
More informationProperties of Matrices
LESSON 5 Properties of Matrices Opening Exercise MATRIX CALCULATOR In Lesson 4, we used the subway and bus line network connecting four cities The bus routes connecting the cities are represented by solid
More informationMatrices and Vectors
Matrices and Vectors James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University November 11, 2013 Outline 1 Matrices and Vectors 2 Vector Details 3 Matrix
More informationDefinition: A binary relation R from a set A to a set B is a subset R A B. Example:
Section 9.1 Rela%onships Relationships between elements of sets occur in many contexts. Every day we deal with relationships such as those between a business and its telephone number, an employee and his
More informationChapter 2. Error Correcting Codes. 2.1 Basic Notions
Chapter 2 Error Correcting Codes The identification number schemes we discussed in the previous chapter give us the ability to determine if an error has been made in recording or transmitting information.
More informationDepartment of Computer Science University at Albany, State University of New York Solutions to Sample Discrete Mathematics Examination II (Fall 2007)
Department of Computer Science University at Albany, State University of New York Solutions to Sample Discrete Mathematics Examination II (Fall 2007) Problem 1: Specify two different predicates P (x) and
More informationMath 4310 Solutions to homework 1 Due 9/1/16
Math 0 Solutions to homework Due 9//6. An element [a] Z/nZ is idempotent if [a] 2 [a]. Find all idempotent elements in Z/0Z and in Z/Z. Solution. First note we clearly have [0] 2 [0] so [0] is idempotent
More information1 Last time: inverses
MATH Linear algebra (Fall 8) Lecture 8 Last time: inverses The following all mean the same thing for a function f : X Y : f is invertible f is one-to-one and onto 3 For each b Y there is exactly one a
More informationToday. Binary relations establish a relationship between elements of two sets
Today Relations Binary relations and properties Relationship to functions n-ary relations Definitions Binary relations establish a relationship between elements of two sets Definition: Let A and B be two
More informationa + b = b + a and a b = b a. (a + b) + c = a + (b + c) and (a b) c = a (b c). a (b + c) = a b + a c and (a + b) c = a c + b c.
Properties of the Integers The set of all integers is the set and the subset of Z given by Z = {, 5, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, }, N = {0, 1, 2, 3, 4, }, is the set of nonnegative integers (also called
More informationProperties of the Integers
Properties of the Integers The set of all integers is the set and the subset of Z given by Z = {, 5, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5, }, N = {0, 1, 2, 3, 4, }, is the set of nonnegative integers (also called
More information1 - Systems of Linear Equations
1 - Systems of Linear Equations 1.1 Introduction to Systems of Linear Equations Almost every problem in linear algebra will involve solving a system of equations. ü LINEAR EQUATIONS IN n VARIABLES We are
More informationRelations. We have seen several types of abstract, mathematical objects, including propositions, predicates, sets, and ordered pairs and tuples.
Relations We have seen several types of abstract, mathematical objects, including propositions, predicates, sets, and ordered pairs and tuples. Relations use ordered tuples to represent relationships among
More informationMath 3191 Applied Linear Algebra
Math 9 Applied Linear Algebra Lecture 9: Diagonalization Stephen Billups University of Colorado at Denver Math 9Applied Linear Algebra p./9 Section. Diagonalization The goal here is to develop a useful
More informationSection 29: What s an Inverse?
Section 29: What s an Inverse? Our investigations in the last section showed that all of the matrix operations had an identity element. The identity element for addition is, for obvious reasons, called
More informationRelations MATH Relations. Benjamin V.C. Collins, James A. Swenson MATH 2730
MATH 2730 Benjamin V.C. Collins James A. Swenson among integers equals a = b is true for some pairs (a, b) Z Z, but not for all pairs. is less than a < b is true for some pairs (a, b) Z Z, but not for
More information1. Vectors.
1. Vectors 1.1 Vectors and Matrices Linear algebra is concerned with two basic kinds of quantities: vectors and matrices. 1.1 Vectors and Matrices Scalars and Vectors - Scalar: a numerical value denoted
More informationOrder of Operations. Real numbers
Order of Operations When simplifying algebraic expressions we use the following order: 1. Perform operations within a parenthesis. 2. Evaluate exponents. 3. Multiply and divide from left to right. 4. Add
More informationEcon Slides from Lecture 7
Econ 205 Sobel Econ 205 - Slides from Lecture 7 Joel Sobel August 31, 2010 Linear Algebra: Main Theory A linear combination of a collection of vectors {x 1,..., x k } is a vector of the form k λ ix i for
More informationCOMP232 - Mathematics for Computer Science
COMP232 - Mathematics for Computer Science Tutorial 11 Ali Moallemi moa ali@encs.concordia.ca Iraj Hedayati h iraj@encs.concordia.ca Concordia University, Fall 2015 Ali Moallemi, Iraj Hedayati COMP232
More informationMODEL ANSWERS TO THE FIRST QUIZ. 1. (18pts) (i) Give the definition of a m n matrix. A m n matrix with entries in a field F is a function
MODEL ANSWERS TO THE FIRST QUIZ 1. (18pts) (i) Give the definition of a m n matrix. A m n matrix with entries in a field F is a function A: I J F, where I is the set of integers between 1 and m and J is
More informationREPLACE ONE ROW BY ADDING THE SCALAR MULTIPLE OF ANOTHER ROW
20 CHAPTER 1 Systems of Linear Equations REPLACE ONE ROW BY ADDING THE SCALAR MULTIPLE OF ANOTHER ROW The last type of operation is slightly more complicated. Suppose that we want to write down the elementary
More informationRelations Graphical View
Introduction Relations Computer Science & Engineering 235: Discrete Mathematics Christopher M. Bourke cbourke@cse.unl.edu Recall that a relation between elements of two sets is a subset of their Cartesian
More informationAdvanced Engineering Mathematics Prof. Pratima Panigrahi Department of Mathematics Indian Institute of Technology, Kharagpur
Advanced Engineering Mathematics Prof. Pratima Panigrahi Department of Mathematics Indian Institute of Technology, Kharagpur Lecture No. # 02 Vector Spaces, Subspaces, linearly Dependent/Independent of
More informationGenerating Permutations and Combinations
Generating Permutations and Combinations March 0, 005 Generating Permutations We have learned that there are n! permutations of {,,, n} It is important in many instances to generate a list of such permutations
More informationSelected Solutions to Even Problems, Part 3
Selected Solutions to Even Problems, Part 3 March 14, 005 Page 77 6. If one selects 101 integers from among {1,,..., 00}, then at least two of these numbers must be consecutive, and therefore coprime (which
More informationSection Summary. Sequences. Recurrence Relations. Summations Special Integer Sequences (optional)
Section 2.4 Section Summary Sequences. o Examples: Geometric Progression, Arithmetic Progression Recurrence Relations o Example: Fibonacci Sequence Summations Special Integer Sequences (optional) Sequences
More informationLinear Algebra 1A - solutions of ex. 8
Linear Algebra 1A - solutions of ex. 8 Sum of subspaces, direct sum (skhum yashar) 1) Let V be a vector space, and let U, W V be two subspaces. (a) Prove that V = U W if and only if the following two statements
More informationMA 3280 Lecture 05 - Generalized Echelon Form and Free Variables. Friday, January 31, 2014.
MA 3280 Lecture 05 - Generalized Echelon Form and Free Variables Friday, January 31, 2014. Objectives: Generalize echelon form, and introduce free variables. Material from Section 3.5 starting on page
More informationNotes. Relations. Introduction. Notes. Relations. Notes. Definition. Example. Slides by Christopher M. Bourke Instructor: Berthe Y.
Relations Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry Spring 2006 Computer Science & Engineering 235 Introduction to Discrete Mathematics Sections 7.1, 7.3 7.5 of Rosen cse235@cse.unl.edu
More informationDynamic Programming. Shuang Zhao. Microsoft Research Asia September 5, Dynamic Programming. Shuang Zhao. Outline. Introduction.
Microsoft Research Asia September 5, 2005 1 2 3 4 Section I What is? Definition is a technique for efficiently recurrence computing by storing partial results. In this slides, I will NOT use too many formal
More informationDetermine whether the following system has a trivial solution or non-trivial solution:
Practice Questions Lecture # 7 and 8 Question # Determine whether the following system has a trivial solution or non-trivial solution: x x + x x x x x The coefficient matrix is / R, R R R+ R The corresponding
More informationNonnegative Matrices I
Nonnegative Matrices I Daisuke Oyama Topics in Economic Theory September 26, 2017 References J. L. Stuart, Digraphs and Matrices, in Handbook of Linear Algebra, Chapter 29, 2006. R. A. Brualdi and H. J.
More informationMath 3191 Applied Linear Algebra
Math 9 Applied Linear Algebra Lecture : Null and Column Spaces Stephen Billups University of Colorado at Denver Math 9Applied Linear Algebra p./8 Announcements Study Guide posted HWK posted Math 9Applied
More informationCS100: DISCRETE STRUCTURES. Lecture 3 Matrices Ch 3 Pages:
CS100: DISCRETE STRUCTURES Lecture 3 Matrices Ch 3 Pages: 246-262 Matrices 2 Introduction DEFINITION 1: A matrix is a rectangular array of numbers. A matrix with m rows and n columns is called an m x n
More informationcse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska
cse303 ELEMENTS OF THE THEORY OF COMPUTATION Professor Anita Wasilewska LECTURE 3 CHAPTER 1 SETS, RELATIONS, and LANGUAGES 6. Closures and Algorithms 7. Alphabets and Languages 8. Finite Representation
More informationWhat are relations? f: A B
What are relations? Ch 9.1 What are relations? Notation Informally, a relation is a set of pairs of objects (or in general, set of n-tuples) that are related to each other by some rule. We will focus first
More informationChapter 9: Relations Relations
Chapter 9: Relations 9.1 - Relations Definition 1 (Relation). Let A and B be sets. A binary relation from A to B is a subset R A B, i.e., R is a set of ordered pairs where the first element from each pair
More information= main diagonal, in the order in which their corresponding eigenvectors appear as columns of E.
3.3 Diagonalization Let A = 4. Then and are eigenvectors of A, with corresponding eigenvalues 2 and 6 respectively (check). This means 4 = 2, 4 = 6. 2 2 2 2 Thus 4 = 2 2 6 2 = 2 6 4 2 We have 4 = 2 0 0
More informationSection Summary. Relations and Functions Properties of Relations. Combining Relations
Chapter 9 Chapter Summary Relations and Their Properties n-ary Relations and Their Applications (not currently included in overheads) Representing Relations Closures of Relations (not currently included
More informationDatabases 2011 The Relational Algebra
Databases 2011 Christian S. Jensen Computer Science, Aarhus University What is an Algebra? An algebra consists of values operators rules Closure: operations yield values Examples integers with +,, sets
More informationMTH 215: Introduction to Linear Algebra
MTH 215: Introduction to Linear Algebra Lecture 5 Jonathan A. Chávez Casillas 1 1 University of Rhode Island Department of Mathematics September 20, 2017 1 LU Factorization 2 3 4 Triangular Matrices Definition
More informationDiscrete Structures: Sample Questions, Exam 2, SOLUTIONS
Discrete Structures: Sample Questions, Exam, SOLUTIONS This is longer than the actual test.) 1. List all the strings over X = {a, b, c} of length or less. λ, a, b, c, aa, ab, ac, ba, bb, bc, ca, cb, cc..
More informationMath 315: Linear Algebra Solutions to Assignment 7
Math 5: Linear Algebra s to Assignment 7 # Find the eigenvalues of the following matrices. (a.) 4 0 0 0 (b.) 0 0 9 5 4. (a.) The characteristic polynomial det(λi A) = (λ )(λ )(λ ), so the eigenvalues are
More informationRecitation 8: Graphs and Adjacency Matrices
Math 1b TA: Padraic Bartlett Recitation 8: Graphs and Adjacency Matrices Week 8 Caltech 2011 1 Random Question Suppose you take a large triangle XY Z, and divide it up with straight line segments into
More informationLinear Equations in Linear Algebra
1 Linear Equations in Linear Algebra 1.3 VECTOR EQUATIONS VECTOR EQUATIONS Vectors in 2 A matrix with only one column is called a column vector, or simply a vector. An example of a vector with two entries
More informationWeek 4-5: Generating Permutations and Combinations
Week 4-5: Generating Permutations and Combinations February 27, 2017 1 Generating Permutations We have learned that there are n! permutations of {1, 2,...,n}. It is important in many instances to generate
More informationConsider an infinite row of dominoes, labeled by 1, 2, 3,, where each domino is standing up. What should one do to knock over all dominoes?
1 Section 4.1 Mathematical Induction Consider an infinite row of dominoes, labeled by 1,, 3,, where each domino is standing up. What should one do to knock over all dominoes? Principle of Mathematical
More informationToday s Menu. Administrativia Two Problems Cutting a Pizza Lighting Rooms
Welcome! L01 Today s Menu Administrativia Two Problems Cutting a Pizza Lighting Rooms Administrativia Course page: https://www.cs.duke.edu/courses/spring13/compsci230/ Who we are: Instructor: TA: UTAs:
More informationChapter 3. Cartesian Products and Relations. 3.1 Cartesian Products
Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing
More informationNAME MATH 304 Examination 2 Page 1
NAME MATH 4 Examination 2 Page. [8 points (a) Find the following determinant. However, use only properties of determinants, without calculating directly (that is without expanding along a column or row
More informationName (please print) Mathematics Final Examination December 14, 2005 I. (4)
Mathematics 513-00 Final Examination December 14, 005 I Use a direct argument to prove the following implication: The product of two odd integers is odd Let m and n be two odd integers Since they are odd,
More informationMath 1324 Review 2(answers) x y 2z R R R
Math Review (answers). Solve the following system using Gauss-Jordan Elimination. y z 6 6 0 5 R R R R R R z 5 y z 6 0 0 0 0 0 0 R R R 0 5 0 0 0 0 0 0 z t Infinitely many solutions given by y 5t where t
More informationMATH 580, midterm exam SOLUTIONS
MATH 580, midterm exam SOLUTIONS Solve the problems in the spaces provided on the question sheets. If you run out of room for an answer, continue on the back of the page or use the Extra space empty page
More informationCSE548, AMS542: Analysis of Algorithms, Spring 2014 Date: May 12. Final In-Class Exam. ( 2:35 PM 3:50 PM : 75 Minutes )
CSE548, AMS54: Analysis of Algorithms, Spring 014 Date: May 1 Final In-Class Exam ( :35 PM 3:50 PM : 75 Minutes ) This exam will account for either 15% or 30% of your overall grade depending on your relative
More informationMatrix Theory and Differential Equations Homework 6 Solutions, 10/5/6
Matrix Theory and Differential Equations Homework 6 Solutions, 0/5/6 Question Find the general solution of the matrix system: x 3y + 5z 8t 5 x + 4y z + t Express your answer in the form of a particulaolution
More informationOptimization Methods in Management Science
Optimization Methods in Management Science MIT 15.05 Recitation 8 TAs: Giacomo Nannicini, Ebrahim Nasrabadi At the end of this recitation, students should be able to: 1. Derive Gomory cut from fractional
More information1.1.1 Algebraic Operations
1.1.1 Algebraic Operations We need to learn how our basic algebraic operations interact. When confronted with many operations, we follow the order of operations: Parentheses Exponentials Multiplication
More informationMath 205, Summer I, Week 4b: Continued. Chapter 5, Section 8
Math 205, Summer I, 2016 Week 4b: Continued Chapter 5, Section 8 2 5.8 Diagonalization [reprint, week04: Eigenvalues and Eigenvectors] + diagonaliization 1. 5.8 Eigenspaces, Diagonalization A vector v
More informationAxioms of Kleene Algebra
Introduction to Kleene Algebra Lecture 2 CS786 Spring 2004 January 28, 2004 Axioms of Kleene Algebra In this lecture we give the formal definition of a Kleene algebra and derive some basic consequences.
More informationDiscrete Structures May 13, (40 points) Define each of the following terms:
Discrete Structures May 13, 2014 Prof Feighn Final Exam 1. (40 points) Define each of the following terms: (a) (binary) relation: A binary relation from a set X to a set Y is a subset of X Y. (b) function:
More informationMath Models of OR: Some Definitions
Math Models of OR: Some Definitions John E. Mitchell Department of Mathematical Sciences RPI, Troy, NY 12180 USA September 2018 Mitchell Some Definitions 1 / 20 Active constraints Outline 1 Active constraints
More informationLINEAR ALGEBRA 1, 2012-I PARTIAL EXAM 3 SOLUTIONS TO PRACTICE PROBLEMS
LINEAR ALGEBRA, -I PARTIAL EXAM SOLUTIONS TO PRACTICE PROBLEMS Problem (a) For each of the two matrices below, (i) determine whether it is diagonalizable, (ii) determine whether it is orthogonally diagonalizable,
More information5 Irreducible representations
Physics 129b Lecture 8 Caltech, 01/1/19 5 Irreducible representations 5.5 Regular representation and its decomposition into irreps To see that the inequality is saturated, we need to consider the so-called
More informationCharacterizations of Strongly Regular Graphs: Part II: Bose-Mesner algebras of graphs. Sung Y. Song Iowa State University
Characterizations of Strongly Regular Graphs: Part II: Bose-Mesner algebras of graphs Sung Y. Song Iowa State University sysong@iastate.edu Notation K: one of the fields R or C X: a nonempty finite set
More informationCIS 375 Intro to Discrete Mathematics Exam 3 (Section M004: Blue) 6 December Points Possible
Name: CIS 375 Intro to Discrete Mathematics Exam 3 (Section M004: Blue) 6 December 2016 Question Points Possible Points Received 1 12 2 14 3 14 4 12 5 16 6 16 7 16 Total 100 Instructions: 1. This exam
More informationAnalysis of Algorithms I: Perfect Hashing
Analysis of Algorithms I: Perfect Hashing Xi Chen Columbia University Goal: Let U = {0, 1,..., p 1} be a huge universe set. Given a static subset V U of n keys (here static means we will never change the
More informationDefinition: A binary relation R from a set A to a set B is a subset R A B. Example:
Chapter 9 1 Binary Relations Definition: A binary relation R from a set A to a set B is a subset R A B. Example: Let A = {0,1,2} and B = {a,b} {(0, a), (0, b), (1,a), (2, b)} is a relation from A to B.
More informationLecture Summaries for Linear Algebra M51A
These lecture summaries may also be viewed online by clicking the L icon at the top right of any lecture screen. Lecture Summaries for Linear Algebra M51A refers to the section in the textbook. Lecture
More information1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det
What is the determinant of the following matrix? 3 4 3 4 3 4 4 3 A 0 B 8 C 55 D 0 E 60 If det a a a 3 b b b 3 c c c 3 = 4, then det a a 4a 3 a b b 4b 3 b c c c 3 c = A 8 B 6 C 4 D E 3 Let A be an n n matrix
More informationLinear Algebra March 16, 2019
Linear Algebra March 16, 2019 2 Contents 0.1 Notation................................ 4 1 Systems of linear equations, and matrices 5 1.1 Systems of linear equations..................... 5 1.2 Augmented
More informationCSL361 Problem set 4: Basic linear algebra
CSL361 Problem set 4: Basic linear algebra February 21, 2017 [Note:] If the numerical matrix computations turn out to be tedious, you may use the function rref in Matlab. 1 Row-reduced echelon matrices
More informationsum of squared error.
IT 131 MATHEMATCS FOR SCIENCE LECTURE NOTE 6 LEAST SQUARES REGRESSION ANALYSIS and DETERMINANT OF A MATRIX Source: Larson, Edwards, Falvo (2009): Elementary Linear Algebra, Sixth Edition You will now look
More informationMatrix compositions. Emanuele Munarini. Dipartimento di Matematica Politecnico di Milano
Matrix compositions Emanuele Munarini Dipartimento di Matematica Politecnico di Milano emanuelemunarini@polimiit Joint work with Maddalena Poneti and Simone Rinaldi FPSAC 26 San Diego Motivation: L-convex
More informationToday s topics. Binary Relations. Inverse Relations. Complementary Relations. Let R:A,B be any binary relation.
Today s topics Binary Relations Relations Kinds of relations n-ary relations Representations of relations Reading: Sections 7.-7.3 Upcoming Upcoming Minesweeper Let A, B be any sets. A binary relation
More information2. Transience and Recurrence
Virtual Laboratories > 15. Markov Chains > 1 2 3 4 5 6 7 8 9 10 11 12 2. Transience and Recurrence The study of Markov chains, particularly the limiting behavior, depends critically on the random times
More informationMath 42, Discrete Mathematics
c Fall 2018 last updated 12/05/2018 at 15:47:21 For use by students in this class only; all rights reserved. Note: some prose & some tables are taken directly from Kenneth R. Rosen, and Its Applications,
More informationCIS 375 Intro to Discrete Mathematics Exam 3 (Section M001: Green) 6 December Points Possible
Name: CIS 375 Intro to Discrete Mathematics Exam 3 (Section M001: Green) 6 December 2016 Question Points Possible Points Received 1 12 2 14 3 14 4 12 5 16 6 16 7 16 Total 100 Instructions: 1. This exam
More informationChapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations
Chapter 1: Systems of linear equations and matrices Section 1.1: Introduction to systems of linear equations Definition: A linear equation in n variables can be expressed in the form a 1 x 1 + a 2 x 2
More informationLecture 23 Branch-and-Bound Algorithm. November 3, 2009
Branch-and-Bound Algorithm November 3, 2009 Outline Lecture 23 Modeling aspect: Either-Or requirement Special ILPs: Totally unimodular matrices Branch-and-Bound Algorithm Underlying idea Terminology Formal
More informationNew Inequalities for q-ary Constant-Weight Codes
New Inequalities for q-ary Constant-Weight Codes Hyun Kwang Kim 1 Phan Thanh Toan 1 1 Department of Mathematics, POSTECH International Workshop on Coding and Cryptography April 15-19, 2013, Bergen (Norway
More informationDRAFT CONCEPTUAL SOLUTION REPORT DRAFT
BASIC STRUCTURAL MODELING PROJECT Joseph J. Simpson Mary J. Simpson 08-12-2013 DRAFT CONCEPTUAL SOLUTION REPORT DRAFT Version 0.11 Page 1 of 18 Table of Contents Introduction Conceptual Solution Context
More informationMath 54 HW 4 solutions
Math 54 HW 4 solutions 2.2. Section 2.2 (a) False: Recall that performing a series of elementary row operations A is equivalent to multiplying A by a series of elementary matrices. Suppose that E,...,
More informationMultiple Choice Questions for Review
Equivalence and Order Multiple Choice Questions for Review In each case there is one correct answer (given at the end of the problem set). Try to work the problem first without looking at the answer. Understand
More informationTMA Calculus 3. Lecture 21, April 3. Toke Meier Carlsen Norwegian University of Science and Technology Spring 2013
TMA4115 - Calculus 3 Lecture 21, April 3 Toke Meier Carlsen Norwegian University of Science and Technology Spring 2013 www.ntnu.no TMA4115 - Calculus 3, Lecture 21 Review of last week s lecture Last week
More informationEconomics 204 Summer/Fall 2011 Lecture 2 Tuesday July 26, 2011 N Now, on the main diagonal, change all the 0s to 1s and vice versa:
Economics 04 Summer/Fall 011 Lecture Tuesday July 6, 011 Section 1.4. Cardinality (cont.) Theorem 1 (Cantor) N, the set of all subsets of N, is not countable. Proof: Suppose N is countable. Then there
More informationRooks and Pascal s Triangle. shading in the first k squares of the diagonal running downwards to the right. We
Roos and Pascal s Triangle An (n,) board consists of n 2 squares arranged in n rows and n columns with shading in the first squares of the diagonal running downwards to the right. We consider (n,) boards
More informationAnnouncements Monday, September 18
Announcements Monday, September 18 WeBWorK 1.4, 1.5 are due on Wednesday at 11:59pm. The first midterm is on this Friday, September 22. Midterms happen during recitation. The exam covers through 1.5. About
More information7.6 The Inverse of a Square Matrix
7.6 The Inverse of a Square Matrix Copyright Cengage Learning. All rights reserved. What You Should Learn Verify that two matrices are inverses of each other. Use Gauss-Jordan elimination to find inverses
More informationFind the following matrix products, if possible.(1-4)
Name: Math 1324 Activity 8(4.5)(Due by Oct. 13) Dear Instructor or Tutor, These problems are designed to let my students show me what they have learned and what they are capable of doing on their own.
More information