The Probability of Winning a Series. Gregory Quenell

Size: px
Start display at page:

Download "The Probability of Winning a Series. Gregory Quenell"

Transcription

1 The Probability of Winning a Series Gregory Quenell

2 Exercise: Team A and Team B play a series of n + games. The first team to win n + games wins the series. All games are independent, and Team A wins any single game with some fixed probability p. What is the probability that Team A wins the series? p p A p p p B AA AB BA BB p p AAA AAB ABA ABB BAA BAB BBA BBB p + p ( p) + p ( p) = p p

3 Exercise: Team A and Team B play a series of n + games. The first team to win n + games wins the series. All games are independent, and Team A wins any single game with some fixed probability p. What is the probability that Team A wins the series? p p A p p p B AA AB BA BB p p p p AAA AAB ABA ABB BAA BAB BBA BBB p + p ( p) + p ( p) + p ( p) = p p

4 Vertical solution for n + games: P (A wins the series) = = = n+ k=n+ n+ k=n+ n+ k=n+ n+ = p n+ P (A wins the series on the k th game) P (A wins n of the first k games) P (A wins the k th game) ( ) k p n ( p) k n p n k=n+ ( ) k ( p) k (n+) n

5 Horizontal solution for n + games: P (A wins the series) = = n+ k=n+ n+ k=n+ P (A wins k of the n + games) ( ) n + p k ( p) n+ k k A B AA AB BA BB AAA AAB ABA ABB BAA BAB BBA BBB

6 The probability that Team A wins a (n+)-game series n+ p n+ k=n+ ( k n ) n+ ( p) k (n+) k=n+ ( n + p (n = 0) p p p (n = ) p p k ) p k ( p) n+ k 0p p + p (n = ) 0p p + p p 8p + 0p 0p (n = ) p 8p + 0p 0p.0 P (A wins) p

7 What are the coefficients? n+ p n+ k=n+ ( k n ) ( p) k (n+) = n+ r=n+ After some messy reindexing, we get [ ( ) r (n+) n+ k=r ( k n ) ( ) ] k (n + ) p r r (n + ) n+ k=n+ ( n + k ) p k ( p) n+ k = n+ r=n+ [ r k=n+ ( n + ( ) r k k ) ( n + k r k ) ] p r

8 A Pascal s triangle relation Equating the coefficients of p r in the vertical and horizontal polynomials, we get a two-parameter family of relations: [ ( ) r (n+) n+ [ r k=n+ ( k n k=r = ( n + ( ) r k k ) ( ) ] k (n + ) r (n + ) ) ( n + k r k for each n and for each r in {n +, n +,..., n + }. ) ] 8

9 ( ) r (n+) n+ k=r ( k n ) ( ) k (n + ) r (n + ) = r k=n+ ( n + ( ) r k k ) ( n + k r k ) Example: n =, r = ( )( ) ( )( ) + 0 ( )( ) + 0 ( )( ) 0 = = ( )( ) 0 9

10 ( ) r (n+) n+ k=r ( k n ) ( ) k (n + ) r (n + ) = r k=n+ ( n + ( ) r k k ) ( n + k r k ) Example: n =, r =. ( )( ) 0 0 ( 0 )( ) ( )( ) = 8 = ( 0 0 )( ) + 0 ( )( ) 0 0

11 ( ) r (n+) n+ k=r ( k n ) ( ) k (n + ) r (n + ) = r k=n+ ( n + ( ) r k k ) ( n + k r k ) Example: n =, r = ( )( ) + ( )( ) = 0 = ( )( ) ( )( ) + ( )( ) 0

12 ( ) r (n+) n+ k=r ( k n ) ( ) k (n + ) r (n + ) = r k=n+ ( n + ( ) r k k ) ( n + k r k ) Example: n =, r =. ( )( ) = 0 = ( )( ) + ( )( ) ( 0 0 )( ) + 0 ( )( ) 0 0

13 Remark: In the boundary case where r = n +, we get the hockey stick relation =

14 Remark: In the other boundary case where r = n +, we get an alternating hockey stick = +

15 Back to the polynomials We translate and scale the functions to get a sequence of odd polynomials on [, ] s 0 (x) = x x x s (x) = s (x) = x 0x + x 8..0

16 Observation This sequence converges pointwise and monotonically to the signum function s 0 (x) = x x x s (x) = s (x) = x 0x + x 8..0

17 Question Can we make this sequence converge to sgn(x) in some vector space of functions on [, ]? That is, can we find a system {φ 0, φ, φ,...} of polynomials on [, ] so that each φ k is a polynomial of degree k + there is an inner product, with φ m, φ n = δ m,n sgn(x) = sgn, φ k φ k (x) k=0 our s n polynomials are the partial sums of this series: s n (x) =? n sgn, φ k φ k (x) k=0

18 First attempt: Use the normalized Legendre polynomials The partial sums converge to sgn(x), but they are not our s n polynomials. 8

19 Second attempt: Use the normalized Chebyshev T polynomials Again, we do not get the monotonic convergence. 9

20 Inconvenient Truth: Our polynomials s n cannot be the partial sums of a series sgn, φk φ k Reason: In such a series, the difference between two partial sums, s n+ s n.0 is a scalar multiple of φ n+, so it must be orthogonal to s n. But in our sequence, s n (x) and s n+ (x) s n (x) always have the same sign, so their inner product s n, s n+ s n = cannot be zero. s n (x)[s n+ (x) s n (x)]w(x) dx 0

21 Question: Why does f, g have the form f(x)g(x)w(x) dx where w is some non-negative weight function? In R n, we can take x, y to be [ x T ] [ ] [ ] A y for any symmetric, positive-definite matrix A (not just a diagonal A). So why not say f, g = where A is symmetric and positive definite? f(x)a(x, y)g(y) dy dx

22 Try this on s 0 (x) = x s (x) s 0 (x) = x( x ) s (x) s (x) = 8 x( x ) s (x) s (x) = x( x ) s (x) s (x) = 8 x( x ) These functions are orthonormal with respect to the inner product f, g = where A is the function graphed above. f(x)a(x, y)g(y) dx dy,

23 Better news: The polynomial s n has the following properties: s n is odd of degree n s n () = s (r) n () = 0 for r =,,..., n

24 Better news: The polynomial s n has the following properties: s n is odd of degree n s n () = s (r) n () = 0 for r =,,..., n Better still, these properties determine s n..0 Example: Write s (x) = a x + a x + a x. Then = s () = a + a + a 0 = s () = a + a + a 0 = s () = a + a a = /8 a = 0/8 a = /8

25 Observation: This makes our s n polynomials look a lot like power-series convergents to the signum function Sort of:.0 An n-coefficient polynomial approximation to a function f is determined by values of f at 0 and ; the right number of derivatives of f at ; and being an odd polynomial.

26 Something else to play with: Here are some even polynomials v n (x) determined by v n (0) = 0; v n () = ; v n() = for n > ; v (r) n = 0 for n > and r v (x) = x v (x) = (x x ) v (x) = 8 (x 0x + x ) v (x) = (0x 0x + x 0x 8 ).

27 Something else to play with: Here are some even polynomials v n (x) determined by v n (0) = 0; v n () = ; v n() = for n > ; v (r) n = 0 for n > and r. And here is an even function with all those same properties v (x) = x v (x) = (x x ) v (x) = 8 (x 0x + x ) v (x) =. (0x 0x + x 0x 8 )

COSE212: Programming Languages. Lecture 1 Inductive Definitions (1)

COSE212: Programming Languages. Lecture 1 Inductive Definitions (1) COSE212: Programming Languages Lecture 1 Inductive Definitions (1) Hakjoo Oh 2017 Fall Hakjoo Oh COSE212 2017 Fall, Lecture 1 September 4, 2017 1 / 9 Inductive Definitions Inductive definition (induction)

More information

COSE212: Programming Languages. Lecture 1 Inductive Definitions (1)

COSE212: Programming Languages. Lecture 1 Inductive Definitions (1) COSE212: Programming Languages Lecture 1 Inductive Definitions (1) Hakjoo Oh 2018 Fall Hakjoo Oh COSE212 2018 Fall, Lecture 1 September 5, 2018 1 / 10 Inductive Definitions Inductive definition (induction)

More information

CS 133 : Automata Theory and Computability

CS 133 : Automata Theory and Computability CS 133 : Automata Theory and Computability Lecture Slides 1 Regular Languages and Finite Automata Nestine Hope S. Hernandez Algorithms and Complexity Laboratory Department of Computer Science University

More information

Semigroup presentations via boundaries in Cayley graphs 1

Semigroup presentations via boundaries in Cayley graphs 1 Semigroup presentations via boundaries in Cayley graphs 1 Robert Gray University of Leeds BMC, Newcastle 2006 1 (Research conducted while I was a research student at the University of St Andrews, under

More information

CSEP 590 Data Compression Autumn Arithmetic Coding

CSEP 590 Data Compression Autumn Arithmetic Coding CSEP 590 Data Compression Autumn 2007 Arithmetic Coding Reals in Binary Any real number x in the interval [0,1) can be represented in binary as.b 1 b 2... where b i is a bit. x 0 0 1 0 1... binary representation

More information

The Binomial Theorem.

The Binomial Theorem. The Binomial Theorem RajeshRathod42@gmail.com The Problem Evaluate (A+B) N as a polynomial in powers of A and B Where N is a positive integer A and B are numbers Example: (A+B) 5 = A 5 +5A 4 B+10A 3 B

More information

Theory of Computer Science

Theory of Computer Science Theory of Computer Science C1. Formal Languages and Grammars Malte Helmert University of Basel March 14, 2016 Introduction Example: Propositional Formulas from the logic part: Definition (Syntax of Propositional

More information

CSCI 340: Computational Models. Regular Expressions. Department of Computer Science

CSCI 340: Computational Models. Regular Expressions. Department of Computer Science CSCI 340: Computational Models Regular Expressions Chapter 4 Department of Computer Science Yet Another New Method for Defining Languages Given the Language: L 1 = {x n for n = 1 2 3...} We could easily

More information

{a, b, c} {a, b} {a, c} {b, c} {a}

{a, b, c} {a, b} {a, c} {b, c} {a} Section 4.3 Order Relations A binary relation is an partial order if it transitive and antisymmetric. If R is a partial order over the set S, we also say, S is a partially ordered set or S is a poset.

More information

Chapter 4. Regular Expressions. 4.1 Some Definitions

Chapter 4. Regular Expressions. 4.1 Some Definitions Chapter 4 Regular Expressions 4.1 Some Definitions Definition: If S and T are sets of strings of letters (whether they are finite or infinite sets), we define the product set of strings of letters to be

More information

Pentagonal quasigroups. 1. Introduction

Pentagonal quasigroups. 1. Introduction Quasigroups and Related Systems 22 (2014), 147 158 Pentagonal quasigroups Stipe Vidak Abstract. The concept of pentagonal quasigroup is introduced as IM-quasigroup satisfying the additional property of

More information

Theory of Computation

Theory of Computation Theory of Computation Lecture #2 Sarmad Abbasi Virtual University Sarmad Abbasi (Virtual University) Theory of Computation 1 / 1 Lecture 2: Overview Recall some basic definitions from Automata Theory.

More information

Homework 4 Solutions. 2. Find context-free grammars for the language L = {a n b m c k : k n + m}. (with n 0,

Homework 4 Solutions. 2. Find context-free grammars for the language L = {a n b m c k : k n + m}. (with n 0, Introduction to Formal Language, Fall 2016 Due: 21-Apr-2016 (Thursday) Instructor: Prof. Wen-Guey Tzeng Homework 4 Solutions Scribe: Yi-Ruei Chen 1. Find context-free grammars for the language L = {a n

More information

The state numbers of a knot

The state numbers of a knot ILDT2014 RIMS, Kyoto University 21 May 2014 The state numbers of a knot Takuji NAKAMURA (Osaka Electro-Communication University) Joint work with Y. NAKANISHI, S. Satoh and Y. Tomiyama (Kobe University)

More information

CSE 105 Homework 1 Due: Monday October 9, Instructions. should be on each page of the submission.

CSE 105 Homework 1 Due: Monday October 9, Instructions. should be on each page of the submission. CSE 5 Homework Due: Monday October 9, 7 Instructions Upload a single file to Gradescope for each group. should be on each page of the submission. All group members names and PIDs Your assignments in this

More information

Discrete Probability

Discrete Probability Discrete Probability Counting Permutations Combinations r- Combinations r- Combinations with repetition Allowed Pascal s Formula Binomial Theorem Conditional Probability Baye s Formula Independent Events

More information

EXAMPLE CFG. L = {a 2n : n 1 } L = {a 2n : n 0 } S asa aa. L = {a n b : n 0 } L = {a n b : n 1 } S asb ab S 1S00 S 1S00 100

EXAMPLE CFG. L = {a 2n : n 1 } L = {a 2n : n 0 } S asa aa. L = {a n b : n 0 } L = {a n b : n 1 } S asb ab S 1S00 S 1S00 100 EXAMPLE CFG L = {a 2n : n 1 } L = {a 2n : n 0 } S asa aa S asa L = {a n b : n 0 } L = {a n b : n 1 } S as b S as ab L { a b : n 0} L { a b : n 1} S asb S asb ab n 2n n 2n L {1 0 : n 0} L {1 0 : n 1} S

More information

C1.1 Introduction. Theory of Computer Science. Theory of Computer Science. C1.1 Introduction. C1.2 Alphabets and Formal Languages. C1.

C1.1 Introduction. Theory of Computer Science. Theory of Computer Science. C1.1 Introduction. C1.2 Alphabets and Formal Languages. C1. Theory of Computer Science March 20, 2017 C1. Formal Languages and Grammars Theory of Computer Science C1. Formal Languages and Grammars Malte Helmert University of Basel March 20, 2017 C1.1 Introduction

More information

Automata Theory Final Exam Solution 08:10-10:00 am Friday, June 13, 2008

Automata Theory Final Exam Solution 08:10-10:00 am Friday, June 13, 2008 Automata Theory Final Exam Solution 08:10-10:00 am Friday, June 13, 2008 Name: ID #: This is a Close Book examination. Only an A4 cheating sheet belonging to you is acceptable. You can write your answers

More information

Matrices BUSINESS MATHEMATICS

Matrices BUSINESS MATHEMATICS Matrices BUSINESS MATHEMATICS 1 CONTENTS Matrices Special matrices Operations with matrices Matrix multipication More operations with matrices Matrix transposition Symmetric matrices Old exam question

More information

Chapter 11: Factoring Polynomials Greatest Common Factor. ca d Factoring When Terms Have a Common Factor. Factor completely. B Å'B * # "& B Ä'B

Chapter 11: Factoring Polynomials Greatest Common Factor. ca d Factoring When Terms Have a Common Factor. Factor completely. B Å'B * # & B Ä'B Chapter 11: Factoring Polynomials Mr. Getso s Algebra Notes Spring 2015 11.1 Greatest Common Factor ca d Factoring When Terms Have a Common Factor 1. Factor completely. B Å'B * "& 2. B Ä B $ ( 3. B ÅB

More information

Harvard CS121 and CSCI E-121 Lecture 2: Mathematical Preliminaries

Harvard CS121 and CSCI E-121 Lecture 2: Mathematical Preliminaries Harvard CS121 and CSCI E-121 Lecture 2: Mathematical Preliminaries Harry Lewis September 5, 2013 Reading: Sipser, Chapter 0 Sets Sets are defined by their members A = B means that for every x, x A iff

More information

Linear Classifiers (Kernels)

Linear Classifiers (Kernels) Universität Potsdam Institut für Informatik Lehrstuhl Linear Classifiers (Kernels) Blaine Nelson, Christoph Sawade, Tobias Scheffer Exam Dates & Course Conclusion There are 2 Exam dates: Feb 20 th March

More information

Finiteness conditions and index in semigroup theory

Finiteness conditions and index in semigroup theory Finiteness conditions and index in semigroup theory Robert Gray University of Leeds Leeds, January 2007 Robert Gray (University of Leeds) 1 / 39 Outline 1 Motivation and background Finiteness conditions

More information

Chapter 20 - Spontaneous Change and Free Energy

Chapter 20 - Spontaneous Change and Free Energy Chapter 20 - Spontaneous Change and Free Energy - the governing laws of the Universe are the three laws of thermodynamics - these can be said in a number of ways but the best paraphrase that I know is:

More information

From p-adic numbers to p-adic words

From p-adic numbers to p-adic words From p-adic numbers to p-adic words Jean-Éric Pin1 1 January 2014, Lorentz Center, Leiden References I S. Eilenberg, Automata, Languages and Machines, Vol B, Acad. Press, New-York (1976). M. Lothaire,

More information

Theory of Computation

Theory of Computation Fall 2002 (YEN) Theory of Computation Midterm Exam. Name:... I.D.#:... 1. (30 pts) True or false (mark O for true ; X for false ). (Score=Max{0, Right- 1 2 Wrong}.) (1) X... If L 1 is regular and L 2 L

More information

FABER Formal Languages, Automata. Lecture 2. Mälardalen University

FABER Formal Languages, Automata. Lecture 2. Mälardalen University CD5560 FABER Formal Languages, Automata and Models of Computation Lecture 2 Mälardalen University 2010 1 Content Languages, g Alphabets and Strings Strings & String Operations Languages & Language Operations

More information

Let p 2 ( t), (2 t k), we have the scaling relation,

Let p 2 ( t), (2 t k), we have the scaling relation, Multiresolution Analysis and Daubechies N Wavelet We have discussed decomposing a signal into its Haar wavelet components of varying frequencies. The Haar wavelet scheme relied on two functions: the Haar

More information

CS Automata, Computability and Formal Languages

CS Automata, Computability and Formal Languages Automata, Computability and Formal Languages Luc Longpré faculty.utep.edu/longpre 1 - Pg 1 Slides : version 3.1 version 1 A. Tapp version 2 P. McKenzie, L. Longpré version 2.1 D. Gehl version 2.2 M. Csűrös,

More information

For the given equation, first find the x-intercept by setting y = 0: Next, find the y-intercept by setting x = 0:

For the given equation, first find the x-intercept by setting y = 0: Next, find the y-intercept by setting x = 0: 1. Find the x- and y-intercepts and graph the equation. 5x + 6y = 30 To find the x- and y-intercepts, set one variable equal to 0, and solve for the other variable. To find the x-intercept, set y = 0 and

More information

Week Some Warm-up Questions

Week Some Warm-up Questions 1 Some Warm-up Questions Week 1-2 Abstraction: The process going from specific cases to general problem. Proof: A sequence of arguments to show certain conclusion to be true. If... then... : The part after

More information

1. 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

1. 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 information

Two-Way Automata and Descriptional Complexity

Two-Way Automata and Descriptional Complexity Two-Way Automata and Descriptional Complexity Giovanni Pighizzini Dipartimento di Informatica Università degli Studi di Milano TCS 2014 Rome, Italy September 1-3, 2014 IFIP TC1, Working Group 1.2, Descriptional

More information

CS A Term 2009: Foundations of Computer Science. Homework 2. By Li Feng, Shweta Srivastava, and Carolina Ruiz.

CS A Term 2009: Foundations of Computer Science. Homework 2. By Li Feng, Shweta Srivastava, and Carolina Ruiz. CS3133 - A Term 2009: Foundations of Computer Science Prof. Carolina Ruiz Homework 2 WPI By Li Feng, Shweta Srivastava, and Carolina Ruiz Chapter 4 Problem 1: (10 Points) Exercise 4.3 Solution 1: S is

More information

The Pure Parsimony Problem

The Pure Parsimony Problem Haplotyping and Minimum Diversity Graphs Courtney Davis - University of Utah - Trinity University Some Genetics Mother Paired Gene Representation Physical Trait ABABBA AAABBB Physical Trait ABA AAA Mother

More information

Prove proposition 68. It states: Let R be a ring. We have the following

Prove proposition 68. It states: Let R be a ring. We have the following Theorem HW7.1. properties: Prove proposition 68. It states: Let R be a ring. We have the following 1. The ring R only has one additive identity. That is, if 0 R with 0 +b = b+0 = b for every b R, then

More information

Author: Vivek Kulkarni ( )

Author: Vivek Kulkarni ( ) Author: Vivek Kulkarni ( vivek_kulkarni@yahoo.com ) Chapter-3: Regular Expressions Solutions for Review Questions @ Oxford University Press 2013. All rights reserved. 1 Q.1 Define the following and give

More information

TAFL 1 (ECS-403) Unit- III. 3.1 Definition of CFG (Context Free Grammar) and problems. 3.2 Derivation. 3.3 Ambiguity in Grammar

TAFL 1 (ECS-403) Unit- III. 3.1 Definition of CFG (Context Free Grammar) and problems. 3.2 Derivation. 3.3 Ambiguity in Grammar TAFL 1 (ECS-403) Unit- III 3.1 Definition of CFG (Context Free Grammar) and problems 3.2 Derivation 3.3 Ambiguity in Grammar 3.3.1 Inherent Ambiguity 3.3.2 Ambiguous to Unambiguous CFG 3.4 Simplification

More information

be the set of complex valued 2π-periodic functions f on R such that

be the set of complex valued 2π-periodic functions f on R such that . Fourier series. Definition.. Given a real number P, we say a complex valued function f on R is P -periodic if f(x + P ) f(x) for all x R. We let be the set of complex valued -periodic functions f on

More information

UNC Charlotte 2004 Algebra with solutions

UNC Charlotte 2004 Algebra with solutions with solutions March 8, 2004 1. Let z denote the real number solution to of the digits of z? (A) 13 (B) 14 (C) 15 (D) 16 (E) 17 3 + x 1 = 5. What is the sum Solution: E. Square both sides twice to get

More information

CCHS Math Unit Exam (Ch 1,2,3) Name: Math for Luiberal Arts (200 Points) 9/23/2014

CCHS Math Unit Exam (Ch 1,2,3) Name: Math for Luiberal Arts (200 Points) 9/23/2014 CCHS Math Unit Exam (Ch 1,2,3) Name: Math for Luiberal Arts (200 Points) 9/23/2014 MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Let U = {q, r,

More information

MATRICES. knowledge on matrices Knowledge on matrix operations. Matrix as a tool of solving linear equations with two or three unknowns.

MATRICES. knowledge on matrices Knowledge on matrix operations. Matrix as a tool of solving linear equations with two or three unknowns. MATRICES After studying this chapter you will acquire the skills in knowledge on matrices Knowledge on matrix operations. Matrix as a tool of solving linear equations with two or three unknowns. List of

More information

Number Theory and Counting Method. Divisors -Least common divisor -Greatest common multiple

Number Theory and Counting Method. Divisors -Least common divisor -Greatest common multiple Number Theory and Counting Method Divisors -Least common divisor -Greatest common multiple Divisors Definition n and d are integers d 0 d divides n if there exists q satisfying n = dq q the quotient, d

More information

STRAND J: TRANSFORMATIONS, VECTORS and MATRICES

STRAND J: TRANSFORMATIONS, VECTORS and MATRICES Mathematics SKE, Strand J STRAND J: TRANSFORMATIONS, VECTORS and MATRICES J4 Matrices Text Contents * * * * Section J4. Matrices: Addition and Subtraction J4.2 Matrices: Multiplication J4.3 Inverse Matrices:

More information

Learning Regular Sets

Learning Regular Sets Learning Regular Sets Author: Dana Angluin Presented by: M. Andreína Francisco Department of Computer Science Uppsala University February 3, 2014 Minimally Adequate Teachers A Minimally Adequate Teacher

More information

1 Inner Product and Orthogonality

1 Inner Product and Orthogonality CSCI 4/Fall 6/Vora/GWU/Orthogonality and Norms Inner Product and Orthogonality Definition : The inner product of two vectors x and y, x x x =.., y =. x n y y... y n is denoted x, y : Note that n x, y =

More information

Example. Addition, subtraction, and multiplication in Z are binary operations; division in Z is not ( Z).

Example. Addition, subtraction, and multiplication in Z are binary operations; division in Z is not ( Z). CHAPTER 2 Groups Definition (Binary Operation). Let G be a set. A binary operation on G is a function that assigns each ordered pair of elements of G an element of G. Note. This condition of assigning

More information

Solutions to Exercises, Section 2.4

Solutions to Exercises, Section 2.4 Instructor s Solutions Manual, Section 2.4 Exercise 1 Solutions to Exercises, Section 2.4 Suppose p(x) = x 2 + 5x + 2, q(x) = 2x 3 3x + 1, s(x) = 4x 3 2. In Exercises 1 18, write the indicated expression

More information

CMSC 330: Organization of Programming Languages. Regular Expressions and Finite Automata

CMSC 330: Organization of Programming Languages. Regular Expressions and Finite Automata CMSC 330: Organization of Programming Languages Regular Expressions and Finite Automata CMSC330 Spring 2018 1 How do regular expressions work? What we ve learned What regular expressions are What they

More information

Inverses. Stephen Boyd. EE103 Stanford University. October 28, 2017

Inverses. Stephen Boyd. EE103 Stanford University. October 28, 2017 Inverses Stephen Boyd EE103 Stanford University October 28, 2017 Outline Left and right inverses Inverse Solving linear equations Examples Pseudo-inverse Left and right inverses 2 Left inverses a number

More information

CS6902 Theory of Computation and Algorithms

CS6902 Theory of Computation and Algorithms CS6902 Theory of Computation and Algorithms Any mechanically (automatically) discretely computation of problem solving contains at least three components: - problem description - computational tool - procedure/analysis

More information

Vectors in Function Spaces

Vectors in Function Spaces Jim Lambers MAT 66 Spring Semester 15-16 Lecture 18 Notes These notes correspond to Section 6.3 in the text. Vectors in Function Spaces We begin with some necessary terminology. A vector space V, also

More information

APPENDIX B GRAM-SCHMIDT PROCEDURE OF ORTHOGONALIZATION. Let V be a finite dimensional inner product space spanned by basis vector functions

APPENDIX B GRAM-SCHMIDT PROCEDURE OF ORTHOGONALIZATION. Let V be a finite dimensional inner product space spanned by basis vector functions 301 APPENDIX B GRAM-SCHMIDT PROCEDURE OF ORTHOGONALIZATION Let V be a finite dimensional inner product space spanned by basis vector functions {w 1, w 2,, w n }. According to the Gram-Schmidt Process an

More information

CMSC 330: Organization of Programming Languages

CMSC 330: Organization of Programming Languages CMSC 330: Organization of Programming Languages Regular Expressions and Finite Automata CMSC 330 Spring 2017 1 How do regular expressions work? What we ve learned What regular expressions are What they

More information

CFG Simplification. (simplify) 1. Eliminate useless symbols 2. Eliminate -productions 3. Eliminate unit productions

CFG Simplification. (simplify) 1. Eliminate useless symbols 2. Eliminate -productions 3. Eliminate unit productions CFG Simplification (simplify) 1. Eliminate useless symbols 2. Eliminate -productions 3. Eliminate unit productions 1 Eliminating useless symbols 1. A symbol X is generating if there exists: X * w, for

More information

Compiler Design. Spring Lexical Analysis. Sample Exercises and Solutions. Prof. Pedro C. Diniz

Compiler Design. Spring Lexical Analysis. Sample Exercises and Solutions. Prof. Pedro C. Diniz Compiler Design Spring 2011 Lexical Analysis Sample Exercises and Solutions Prof. Pedro C. Diniz USC / Information Sciences Institute 4676 Admiralty Way, Suite 1001 Marina del Rey, California 90292 pedro@isi.edu

More information

Concordia University Department of Computer Science & Software Engineering

Concordia University Department of Computer Science & Software Engineering Concordia University Department of Computer Science & Software Engineering COMP 335/4 Theoretical Computer Science Winter 2015 Assignment 3 1. In each case, what language is generated by CFG s below. Justify

More information

In English, there are at least three different types of entities: letters, words, sentences.

In English, there are at least three different types of entities: letters, words, sentences. Chapter 2 Languages 2.1 Introduction In English, there are at least three different types of entities: letters, words, sentences. letters are from a finite alphabet { a, b, c,..., z } words are made up

More information

Summary of Last Lectures

Summary of Last Lectures Lossless Coding IV a k p k b k a 0.16 111 b 0.04 0001 c 0.04 0000 d 0.16 110 e 0.23 01 f 0.07 1001 g 0.06 1000 h 0.09 001 i 0.15 101 100 root 1 60 1 0 0 1 40 0 32 28 23 e 17 1 0 1 0 1 0 16 a 16 d 15 i

More information

* is a row matrix * An mxn matrix is a square matrix if and only if m=n * A= is a diagonal matrix if = 0 i

* is a row matrix * An mxn matrix is a square matrix if and only if m=n * A= is a diagonal matrix if = 0 i CET MATRICES *A matrix is an order rectangular array of numbers * A matrix having m rows and n columns is called mxn matrix of order * is a column matrix * is a row matrix * An mxn matrix is a square matrix

More information

Intrusion Detection and Malware Analysis

Intrusion Detection and Malware Analysis Intrusion Detection and Malware Analysis IDS feature extraction Pavel Laskov Wilhelm Schickard Institute for Computer Science Metric embedding of byte sequences Sequences 1. blabla blubla blablabu aa 2.

More information

Valence automata over E-unitary inverse semigroups

Valence automata over E-unitary inverse semigroups Valence automata over E-unitary inverse semigroups Erzsi Dombi 30 May 2018 Outline Motivation Notation and introduction Valence automata Bicyclic and polycyclic monoids Motivation Chomsky-Schützenberger

More information

SFWR ENG 2FA3. Solution to the Assignment #4

SFWR ENG 2FA3. Solution to the Assignment #4 SFWR ENG 2FA3. Solution to the Assignment #4 Total = 131, 100%= 115 The solutions below are often very detailed on purpose. Such level of details is not required from students solutions. Some questions

More information

Algebra I. Book 2. Powered by...

Algebra I. Book 2. Powered by... Algebra I Book 2 Powered by... ALGEBRA I Units 4-7 by The Algebra I Development Team ALGEBRA I UNIT 4 POWERS AND POLYNOMIALS......... 1 4.0 Review................ 2 4.1 Properties of Exponents..........

More information

Fundamentele Informatica II

Fundamentele Informatica II Fundamentele Informatica II Answer to selected exercises 5 John C Martin: Introduction to Languages and the Theory of Computation M.M. Bonsangue (and J. Kleijn) Fall 2011 5.1.a (q 0, ab, Z 0 ) (q 1, b,

More information

A canonical semi-deterministic transducer

A canonical semi-deterministic transducer A canonical semi-deterministic transducer Achilles A. Beros Joint work with Colin de la Higuera Laboratoire d Informatique de Nantes Atlantique, Université de Nantes September 18, 2014 The Results There

More information

Recall: Dot product on R 2 : u v = (u 1, u 2 ) (v 1, v 2 ) = u 1 v 1 + u 2 v 2, u u = u u 2 2 = u 2. Geometric Meaning:

Recall: Dot product on R 2 : u v = (u 1, u 2 ) (v 1, v 2 ) = u 1 v 1 + u 2 v 2, u u = u u 2 2 = u 2. Geometric Meaning: Recall: Dot product on R 2 : u v = (u 1, u 2 ) (v 1, v 2 ) = u 1 v 1 + u 2 v 2, u u = u 2 1 + u 2 2 = u 2. Geometric Meaning: u v = u v cos θ. u θ v 1 Reason: The opposite side is given by u v. u v 2 =

More information

Basics of WQO theory, with some applications in computer science

Basics of WQO theory, with some applications in computer science Basics of WQO theory, with some applications in computer science aka WQOs for dummies Ph. Schnoebelen LSV, CNRS, Cachan CMI Silver Jubilee Lecture Chennai, Feb. 23rd, 2015 INTRODUCTION Well-quasi-orderings,

More information

Section 1.3 Ordered Structures

Section 1.3 Ordered Structures Section 1.3 Ordered Structures Tuples Have order and can have repetitions. (6,7,6) is a 3-tuple () is the empty tuple A 2-tuple is called a pair and a 3-tuple is called a triple. We write (x 1,, x n )

More information

Exponential Generating Functions - J. T. Butler

Exponential Generating Functions - J. T. Butler Epoetal Geeatg Fuctos - J. T. Butle Epoetal Geeatg Fuctos Geeatg fuctos fo pemutatos. Defto: a +a +a 2 2 + a + s the oday geeatg fucto fo the sequece of teges (a, a, a 2, a, ). Ep. Ge. Fuc.- J. T. Butle

More information

Isolation and Contentment in Segregation Games with Three Types

Isolation and Contentment in Segregation Games with Three Types Student Projects Isolation and Contentment in Segregation Games with Three Types Mark Burek, Brian McDonough, Spencer Roach Mark Burek is finishing up his undergraduate work in mathematics at Valparaiso

More information

Linear Systems and Matrices

Linear Systems and Matrices Department of Mathematics The Chinese University of Hong Kong 1 System of m linear equations in n unknowns (linear system) a 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.......

More information

Monoids and Their Cayley Graphs

Monoids and Their Cayley Graphs Monoids and Their Cayley Graphs Nik Ruskuc nik@mcs.st-and.ac.uk School of Mathematics and Statistics, University of St Andrews NBGGT, Leeds, 30 April, 2008 Instead of an Apology Then, as for the geometrical

More information

Final A. Problem Points Score Total 100. Math115A Nadja Hempel 03/23/2017

Final A. Problem Points Score Total 100. Math115A Nadja Hempel 03/23/2017 Final A Math115A Nadja Hempel 03/23/2017 nadja@math.ucla.edu Name: UID: Problem Points Score 1 10 2 20 3 5 4 5 5 9 6 5 7 7 8 13 9 16 10 10 Total 100 1 2 Exercise 1. (10pt) Let T : V V be a linear transformation.

More information

14 Fourier analysis. Read: Boas Ch. 7.

14 Fourier analysis. Read: Boas Ch. 7. 14 Fourier analysis Read: Boas Ch. 7. 14.1 Function spaces A function can be thought of as an element of a kind of vector space. After all, a function f(x) is merely a set of numbers, one for each point

More information

[Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty.]

[Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty.] Math 43 Review Notes [Disclaimer: This is not a complete list of everything you need to know, just some of the topics that gave people difficulty Dot Product If v (v, v, v 3 and w (w, w, w 3, then the

More information

Tense Operators on Basic Algebras

Tense Operators on Basic Algebras Int J Theor Phys (2011) 50:3737 3749 DOI 10.1007/s10773-011-0748-4 Tense Operators on Basic Algebras M. Botur I. Chajda R. Halaš M. Kolařík Received: 10 November 2010 / Accepted: 2 March 2011 / Published

More information

Least Squares. Tom Lyche. October 26, Centre of Mathematics for Applications, Department of Informatics, University of Oslo

Least Squares. Tom Lyche. October 26, Centre of Mathematics for Applications, Department of Informatics, University of Oslo Least Squares Tom Lyche Centre of Mathematics for Applications, Department of Informatics, University of Oslo October 26, 2010 Linear system Linear system Ax = b, A C m,n, b C m, x C n. under-determined

More information

CSEP 521 Applied Algorithms Spring Statistical Lossless Data Compression

CSEP 521 Applied Algorithms Spring Statistical Lossless Data Compression CSEP 52 Applied Algorithms Spring 25 Statistical Lossless Data Compression Outline for Tonight Basic Concepts in Data Compression Entropy Prefix codes Huffman Coding Arithmetic Coding Run Length Coding

More information

Tuesday, September 29, Page 453. Problem 5

Tuesday, September 29, Page 453. Problem 5 Tuesday, September 9, 15 Page 5 Problem 5 Problem. Set up and evaluate the integral that gives the volume of the solid formed by revolving the region bounded by y = x, y = x 5 about the x-axis. Solution.

More information

Stream Codes. 6.1 The guessing game

Stream Codes. 6.1 The guessing game About Chapter 6 Before reading Chapter 6, you should have read the previous chapter and worked on most of the exercises in it. We ll also make use of some Bayesian modelling ideas that arrived in the vicinity

More information

Linear Algebra. Session 12

Linear Algebra. Session 12 Linear Algebra. Session 12 Dr. Marco A Roque Sol 08/01/2017 Example 12.1 Find the constant function that is the least squares fit to the following data x 0 1 2 3 f(x) 1 0 1 2 Solution c = 1 c = 0 f (x)

More information

Talen en Compilers. Johan Jeuring , period 2. October 29, Department of Information and Computing Sciences Utrecht University

Talen en Compilers. Johan Jeuring , period 2. October 29, Department of Information and Computing Sciences Utrecht University Talen en Compilers 2015-2016, period 2 Johan Jeuring Department of Information and Computing Sciences Utrecht University October 29, 2015 12. LL parsing 12-1 This lecture LL parsing Motivation Stack-based

More information

O C C W S M N N Z C Z Y D D C T N P C G O M P C O S B V Y B C S E E K O U T T H E H I D D E N T R E A S U R E S O F L I F E

O C C W S M N N Z C Z Y D D C T N P C G O M P C O S B V Y B C S E E K O U T T H E H I D D E N T R E A S U R E S O F L I F E Timed question: I VISUALIZE A TIME WHEN WE WILL BE TO ROBOTS WHAT DOGS ARE TO HUMANS. AND I AM ROOTING FOR THE MACHINES. 1) S E E K O U T T H E H I D D E N T R E A S U R E S O F L I F E Here s how we get

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I ICS4: Discrete Mathematics for Computer Science I Dept. Information & Computer Sci., Jan Stelovsky based on slides by Dr. Baek and Dr. Still Originals by Dr. M. P. Frank and Dr. J.L. Gross Provided by

More information

Name: Date: Practice Midterm Exam Sections 1.2, 1.3, , ,

Name: Date: Practice Midterm Exam Sections 1.2, 1.3, , , Name: Date: Practice Midterm Exam Sections 1., 1.3,.1-.7, 6.1-6.5, 8.1-8.7 a108 Please develop your one page formula sheet as you try these problems. If you need to look something up, write it down on

More information

Knowledge Discovery and Data Mining 1 (VO) ( )

Knowledge Discovery and Data Mining 1 (VO) ( ) Knowledge Discovery and Data Mining 1 (VO) (707.003) Review of Linear Algebra Denis Helic KTI, TU Graz Oct 9, 2014 Denis Helic (KTI, TU Graz) KDDM1 Oct 9, 2014 1 / 74 Big picture: KDDM Probability Theory

More information

A Tiling Approach to Chebyshev Polynomials

A Tiling Approach to Chebyshev Polynomials A Tiling Approach to Chebyshev Polynomials Daniel Walton Arthur T. Benjamin, Advisor Sanjai Gupta, Reader May, 2007 Department of Mathematics Copyright c 2007 Daniel Walton. The author grants Harvey Mudd

More information

Constructing Lower Bounds on the Derivational Complexity of Rewrite Systems

Constructing Lower Bounds on the Derivational Complexity of Rewrite Systems Constructing Lower Bounds on the Derivational Complexity of Rewrite Systems Dieter Hofbauer, BA Nordhessen, Germany Johannes Waldmann, HTWK Leipzig, Germany Proof Theory and Rewriting, Obergurgl, March

More information

1 Ordinary points and singular points

1 Ordinary points and singular points Math 70 honors, Fall, 008 Notes 8 More on series solutions, and an introduction to \orthogonal polynomials" Homework at end Revised, /4. Some changes and additions starting on page 7. Ordinary points and

More information

Topics in Timed Automata

Topics in Timed Automata 1/32 Topics in Timed Automata B. Srivathsan RWTH-Aachen Software modeling and Verification group 2/32 Timed Automata A theory of timed automata R. Alur and D. Dill, TCS 94 2/32 Timed Automata Language

More information

Equivalence, Order, and Inductive Proof

Equivalence, Order, and Inductive Proof 2/ chapter 4 Equivalence, Order, and Inductive Proof Good order is the foundation of all things. Edmund Burke (729 797) Classifying things and ordering things are activities in which we all engage from

More information

Decomposition of Complete Tripartite Graphs Into 5-Cycles

Decomposition of Complete Tripartite Graphs Into 5-Cycles Decomposition of Complete Tripartite Graphs Into 5-Cycles E.S. MAHMOODIAN MARYAM MIRZAKHANI Department of Mathematical Sciences Sharif University of Technology P.O. Box 11365 9415 Tehran, I.R. Iran emahmood@irearn.bitnet

More information

STEP Support Programme. Statistics STEP Questions: Solutions

STEP Support Programme. Statistics STEP Questions: Solutions STEP Support Programme Statistics STEP Questions: Solutions 200 S Q2 Preparation (i) (a) The sum of the probabilities is, so we have k + 2k + 3k + 4k k 0. (b) P(X 3) P(X 3) + P(X 4) 7 0. (c) E(X) 0 ( +

More information

Multiplying Products of Prime Powers

Multiplying Products of Prime Powers Problem 1: Multiplying Products of Prime Powers Each positive integer can be expressed (in a unique way, according to the Fundamental Theorem of Arithmetic) as a product of powers of the prime numbers.

More information

CS250, Fall 2010, Midterm 2, Tuesday November 9, 8am.

CS250, Fall 2010, Midterm 2, Tuesday November 9, 8am. CS250, Fall 2010, Midterm 2, Tuesday November 9, 8am. This is an individual, closed-book (and notes, cell phone,...) exam. You have 75 minutes. Write CS250 in the Subject and #1 in the Test No. fields

More information

1. 10 apples for $6 is $0.60 per apple. 20 apples for $10 is $0.50 per apple. 25 $ $0.50 = 25 $0.10 = $2.50

1. 10 apples for $6 is $0.60 per apple. 20 apples for $10 is $0.50 per apple. 25 $ $0.50 = 25 $0.10 = $2.50 Fall 205. 0 apples for $6 is $0.60 per apple. 20 apples for $0 is $0.50 per apple. So the answer is B. $2.50 25 $0.60 25 $0.50 = 25 $0.0 = $2.50 2. Let s begin by finding the slopes of the two lines. ax

More information

Exercise Set Suppose that A, B, C, D, and E are matrices with the following sizes: A B C D E

Exercise Set Suppose that A, B, C, D, and E are matrices with the following sizes: A B C D E Determine the size of a given matrix. Identify the row vectors and column vectors of a given matrix. Perform the arithmetic operations of matrix addition, subtraction, scalar multiplication, and multiplication.

More information

arxiv: v1 [math.ra] 15 Jul 2013

arxiv: v1 [math.ra] 15 Jul 2013 Additive Property of Drazin Invertibility of Elements Long Wang, Huihui Zhu, Xia Zhu, Jianlong Chen arxiv:1307.3816v1 [math.ra] 15 Jul 2013 Department of Mathematics, Southeast University, Nanjing 210096,

More information