Solving Linear Recurrence Relations. Niloufar Shafiei
|
|
- Mariah Chandler
- 7 years ago
- Views:
Transcription
1 Solving Linear Recurrence Relations Niloufar Shafiei
2 Review A recursive definition of a sequence specifies Initial conditions Recurrence relation Example: a 0 =0 and a 1 =3 Initial conditions a n = 2a n-1 - a n-2 a n = 3n Recurrence relation Solution 1
3 Linear recurrences Linear recurrence: Each term of a sequence is a linear function of earlier terms in the sequence. For example: a 0 = 1 a 1 = 6 a 2 = 10 a n = a n-1 + 2a n-2 + 3a n-3 a 3 = a 0 + 2a 1 + 3a 2 = 1 + 2(6) + 3(10) = 43 2
4 Linear recurrences Linear recurrences 1. Linear homogeneous recurrences 2. Linear non-homogeneous recurrences 3
5 Linear homogeneous recurrences A linear homogenous recurrence relation of degree k with constant coefficients is a recurrence relation of the form a n = c 1 a n-1 + c 2 a n c k a n-k, where c 1, c 2,, c k are real numbers, and c k 0. a n is expressed in terms of the previous k terms of the sequence, so its degree is k. This recurrence includes k initial conditions. a 0 = C 0 a 1 = C 1 a k = C k 4
6 Example Determine if the following recurrence relations are linear homogeneous recurrence relations with constant coefficients. P n = (1.11)P n-1 a linear homogeneous recurrence relation of degree one a n = a n-1 + a 2 n-2 not linear f n = f n-1 + f n-2 a linear homogeneous recurrence relation of degree two H n = 2H n-1 +1 not homogeneous a n = a n-6 a linear homogeneous recurrence relation of degree six B n = nb n-1 does not have constant coefficient 5
7 Solving linear homogeneous recurrences Proposition 1: Let a n = c 1 a n-1 + c 2 a n c k a n-k be a linear homogeneous recurrence. Assume the sequence a n satisfies the recurrence. Assume the sequence a n also satisfies the recurrence. So, b n = a n + a n and d n = a n are also sequences that satisfy the recurrence. ( is any constant) Proof: b n = a n + a n = (c 1 a n-1 + c 2 a n c k a n-k ) + (c 1 a n-1 + c 2 a n c k a n-k ) = c 1 (a n-1 + a n-1 ) + c 2 (a n-2 + a n-2 ) + + c k (a n-k + a n-k ) = c 1 b n-1 + c 2 b n c k b n-k So, b n is a solution of the recurrence. 6
8 Solving linear homogeneous recurrences Proposition 1: Let a n = c 1 a n-1 + c 2 a n c k a n-k be a linear homogeneous recurrence. Assume the sequence a n satisfies the recurrence. Assume the sequence a n also satisfies the recurrence. So, b n = a n + a n and d n = a n are also sequences that satisfy the recurrence. ( is any constant) Proof: d n = a n = (c 1 a n-1 + c 2 a n c k a n-k ) = c 1 ( a n-1 ) + c 2 ( a n-2 ) + + c k ( a n-k ) = c 1 d n-1 + c 2 d n c k d n-k So, d n is a solution of the recurrence. 7
9 Solving linear homogeneous recurrences It follows from the previous proposition, if we find some solutions to a linear homogeneous recurrence, then any linear combination of them will also be a solution to the linear homogeneous recurrence. 8
10 Solving linear homogeneous recurrences Geometric sequences come up a lot when solving linear homogeneous recurrences. So, try to find any solution of the form a n = r n that satisfies the recurrence relation. 9
11 Solving linear homogeneous recurrences Recurrence relation a n = c 1 a n-1 + c 2 a n c k a n-k Try to find a solution of form r n r n = c 1 r n-1 + c 2 r n c k r n-k r n - c 1 r n-1 - c 2 r n c k r n-k = 0 r k - c 1 r k-1 - c 2 r k c k = 0 (dividing both sides by r n-k ) This equation is called the characteristic equation. 10
12 Example Example: The Fibonacci recurrence is F n = F n-1 + F n-2 Its characteristic equation is r 2 - r - 1 = 0 11
13 Solving linear homogeneous recurrences Proposition 2: r is a solution of r k - c 1 r k-1 - c 2 r k c k = 0 if and only if r n is a solution of a n = c 1 a n-1 + c 2 a n c k a n-k. Example: consider the characteristic equation r 2-4r + 4 = 0. r 2-4r + 4 = (r - 2) 2 = 0 So, r=2. So, 2 n satisfies the recurrence F n = 4F n-1-4f n-2. 2 n = 4. 2 n n-2 2 n-2 ( ) = 0 12
14 Solving linear homogeneous recurrences Theorem 1: Consider the characteristic equation r k - c 1 r k-1 - c 2 r k c k = 0 and the recurrence a n = c 1 a n-1 + c 2 a n c k a n-k. Assume r 1, r 2, and r m all satisfy the equation. Let 1, 2,, m be any constants. So, a n = 1 r n r n m r n m satisfies the recurrence. Proof: By Proposition 2, i r i n satisfies the recurrence. So, by Proposition 1, i i r i n satisfies the recurrence. Applying Proposition 1 again, the sequence a n = 1 r 1 n + 2 r 2 n + + m r m n satisfies the recurrence. 13
15 Example What is the solution of the recurrence relation a n = a n-1 + 2a n-2 with a 0 =2 and a 1 =7? Solution: Since it is linear homogeneous recurrence, first find its characteristic equation r 2 - r - 2 = 0 (r+1)(r-2) = 0 r 1 = 2 and r 2 = -1 So, by theorem a n = 1 2 n + 2 (-1) n is a solution. Now we should find 1 and 2 using initial conditions. a 0 = = 2 a 1 = (-1) = 7 So, 1 = 3 and 2 = -1. a n = 3. 2 n - (-1) n is a solution. 14
16 Example What is the solution of the recurrence relation f n = f n-1 + f n-2 with f 0 =0 and f 1 =1? Solution: Since it is linear homogeneous recurrence, first find its characteristic equation r 2 - r - 1 = 0 r 1 = (1+ )/2 and r 2 = (1- )/2 So, by theorem f n = 1 ((1+ )/2) n + 2 ((1- )/2) n is a solution. Now we should find 1 and 2 using initial conditions. f 0 = = 0 f 1 = 1 (1+ )/2 + 2 (1- )/2 = 1 So, 1 = 1/ and 2 = -1/. a n = 1/. ((1+ )/2) n - 1/ ((1- )/2) n is a solution. 15
17 Example What is the solution of the recurrence relation a n = -a n-1 + 4a n-2 + 4a n-3 with a 0 =8, a 1 =6 and a 2 =26? Solution: Since it is linear homogeneous recurrence, first find its characteristic equation r 3 + r 2-4r - 4 = 0 (r+1)(r+2)(r-2) = 0 r 1 = -1, r 2 = -2 and r 3 = 2 So, by theorem a n = 1 (-1) n + 2 (-2) n n is a solution. Now we should find 1, 2 and 3 using initial conditions. a 0 = = 8 a 1 = = 6 a 2 = = 26 So, 1 = 2, 2 = 1 and 3 = 5. a n = 2. (-1) n + (-2) n n is a solution. 16
18 Solving linear homogeneous recurrences If the characteristic equation has k distinct solutions r 1, r 2,, r k, it can be written as (r - r 1 )(r - r 2 ) (r - r k ) = 0. If, after factoring, the equation has m+1 factors of (r - r 1 ), for example, r 1 is called a solution of the characteristic equation with multiplicity m+1. When this happens, not only r 1 n is a solution, but also nr 1n, n 2 r 1n, and n m r 1 n are solutions of the recurrence. 17
19 Solving linear homogeneous recurrences Proposition 3: Assume r 0 is a solution of the characteristic equation with multiplicity at least m+1. So, n m r n 0 is a solution to the recurrence. 18
20 Solving linear homogeneous recurrences When a characteristic equation has fewer than k distinct solutions: We obtain sequences of the form described in Proposition 3. By Proposition 1, we know any combination of these solutions is also a solution to the recurrence. We can find those that satisfies the initial conditions. 19
21 Solving linear homogeneous recurrences Theorem 2: Consider the characteristic equation r k - c 1 r k-1 - c 2 r k c k = 0 and the recurrence a n = c 1 a n-1 + c 2 a n c k a n-k. Assume the characteristic equation has t k distinct solutions. Let i (1 i t) r i with multiplicity m i be a solution of the equation. Let i,j (1 i t and 0 j m i -1) ij be a constant. So, a n = ( n+ + 1,m1-1 nm 1-1 ) r n 1 + ( n+ + 2,m2-1 nm 2-1 ) r 2 n + + ( t0 + t1 n+ + t,mt -1 nm t -1 ) r t n satisfies the recurrence. 20
22 Example What is the solution of the recurrence relation a n = 6a n-1-9a n-2 with a 0 =1 and a 1 =6? Solution: First find its characteristic equation r 2-6r + 9 = 0 (r - 3) 2 = 0 r 1 = 3 (Its multiplicity is 2.) So, by theorem a n = ( n)(3) n is a solution. Now we should find constants using initial conditions. a 0 = 10 = 1 a 1 = = 6 So, 11 = 1 and 10 = 1. a n = 3 n + n3 n is a solution. 21
23 Example What is the solution of the recurrence relation a n = -3a n-1-3a n-2 - a n-3 with a 0 =1, a 1 =-2 and a 2 =-1? Solution: Find its characteristic equation r 3 + 3r 2 + 3r + 1 = 0 (r + 1) 3 = 0 r 1 = -1 (Its multiplicity is 3.) So, by theorem a n = ( n + 12 n 2 )(-1) n is a solution. Now we should find constants using initial conditions. a 0 = 10 = 1 a 1 = = -2 a 2 = = -1 So, 10 = 1, 11 = 3 and 12 = -2. a n = (1 + 3n - 2n 2 ) (-1) n is a solution. 22
24 Example What is the solution of the recurrence relation a n = 8a n-2-16a n-4, for n 4, with a 0 =1, a 1 =4, a 2 =28 and a 3 =32? Solution: Find its characteristic equation r 4-8r = 0 (r 2-4) 2 = (r-2) 2 (r+2) 2 = 0 r 1 = 2 r 2 = -2 (Their multiplicities are 2.) So, by theorem a n = ( n)(2) n + ( n)(-2) n is a solution. Now we should find constants using initial conditions. a 0 = = 1 a 1 = = 4 a 2 = = 28 a 3 = = 32 So, 10 = 1, 11 = 2, 20 = 0 and 21 = 1. a n = (1 + 2n) 2 n + n (-2) n is a solution. 23
25 Linear non-homogeneous recurrences A linear non-homogenous recurrence relation with constant coefficients is a recurrence relation of the form a n = c 1 a n-1 + c 2 a n c k a n-k + f(n), where c 1, c 2,, c k are real numbers, and f(n) is a function depending only on n. The recurrence relation a n = c 1 a n-1 + c 2 a n c k a n-k, is called the associated homogeneous recurrence relation. This recurrence includes k initial conditions. a 0 = C 0 a 1 = C 1 a k = C k 24
26 Example The following recurrence relations are linear nonhomogeneous recurrence relations. a n = a n n a n = a n-1 + a n-2 + n 2 + n + 1 a n = a n-1 + a n-4 + n! a n = a n-6 + n2 n 25
27 Linear non-homogeneous recurrences Proposition 4: Let a n = c 1 a n-1 + c 2 a n c k a n-k + f(n) be a linear non-homogeneous recurrence. Assume the sequence b n satisfies the recurrence. Another sequence a n satisfies the nonhomogeneous recurrence if and only if h n = a n - b n is also a sequence that satisfies the associated homogeneous recurrence. 26
28 Linear non-homogeneous recurrences Proof: Part1: if h n satisfies the associated homogeneous recurrence then a n is satisfies the non-homogeneous recurrence. b n = c 1 b n-1 + c 2 b n c k b n-k + f(n) h n = c 1 h n-1 + c 2 h n c k h n-k b n + h n = c 1 (b n-1 + h n-1 ) + c 2 (b n-2 + h n-2 ) + + c k (b n-k + h n-k ) + f(n) Since a n = b n + h n, a n = c 1 a n-1 + c 2 a n c k a n-k + f(n). So, a n is a solution of the non-homogeneous recurrence. 27
29 Linear non-homogeneous recurrences Proof: Part2: if a n satisfies the non-homogeneous recurrence then h n is satisfies the associated homogeneous recurrence. b n = c 1 b n-1 + c 2 b n c k b n-k + f(n) a n = c 1 a n-1 + c 2 a n c k a n-k + f(n) a n - b n = c 1 (a n-1 - b n-1 ) + c 2 (a n-2 - b n-2 ) + + c k (a n-k - b n-k ) Since h n = a n - b n, h n = c 1 h n-1 + c 2 h n c k h n-k So, h n is a solution of the associated homogeneous recurrence. 28
30 Linear non-homogeneous recurrences Proposition 4: Let a n = c 1 a n-1 + c 2 a n c k a n-k + f(n) be a linear nonhomogeneous recurrence. Assume the sequence b n satisfies the recurrence. Another sequence a n satisfies the non-homogeneous recurrence if and only if h n = a n - b n is also a sequence that satisfies the associated homogeneous recurrence. We already know how to find h n. For many common f(n), a solution b n to the non-homogeneous recurrence is similar to f(n). Then you should find solution a n = b n + h n to the nonhomogeneous recurrence that satisfies both recurrence and initial conditions. 29
31 Example What is the solution of the recurrence relation a n = a n-1 + a n-2 + 3n + 1 for n 2, with a 0 =2 and a 1 =3? Solution: Since it is linear non-homogeneous recurrence, b n is similar to f(n) Guess: b n = cn + d b n = b n-1 + b n-2 + 3n + 1 cn + d = c(n-1) + d + c(n-2) + d + 3n + 1 cn + d = cn - c + d + cn -2c + d +3n = (3+c)n + (d-3c+1) c = -3 d=-10 So, b n = - 3n (b n only satisfies the recurrence, it does not satisfy the initial conditions.) 30
32 Example What is the solution of the recurrence relation a n = a n-1 + a n-2 + 3n + 1 for n 2, with a 0 =2 and a 1 =3? Solution: We are looking for a n that satisfies both recurrence and initial conditions. a n = b n + h n where h n is a solution for the associated homogeneous recurrence: h n = h n-1 + h n-2 By previous example, we know h n = 1 ((1+ )/2) n + 2 ((1- )/2) n. a n = b n + h n = - 3n ((1+ )/2) n + 2 ((1- )/2) n Now we should find constants using initial conditions. a 0 = = 2 a 1 = (1+ )/2 + 2 (1- )/2 = 3 1 = = 6-2 So, a n = -3n (6 + 2 )((1+ )/2) n + (6-2 )((1- )/2) n. 31
33 Example What is the solution of the recurrence relation a n = 2a n-1 - a n n for n 2, with a 0 =1 and a 1 =2? Solution: Since it is linear non-homogeneous recurrence, b n is similar to f(n) Guess: b n = c2 n + d b n = 2b n-1 - b n n c2 n + d = 2(c2 n-1 + d) - (c2 n-2 + d) + 2 n c2 n + d = c2 n + 2d - c2 n-2 - d + 2 n 0 = (-4c + 4c - c + 4)2 n-2 + (-d + 2d -d) c = 4 d=0 So, b n = 4. 2 n. (b n only satisfies the recurrence, it does not satisfy the initial conditions.) 32
34 Example What is the solution of the recurrence relation a n = 2a n-1 - a n n for n 2, with a 0 =1 and a 1 =2? Solution: We are looking for a n that satisfies both recurrence and initial conditions. a n = b n + h n where h n is a solution for the associated homogeneous recurrence: h n = 2h n-1 - h n-2. Find its characteristic equation r 2-2r + 1 = 0 (r - 1) 2 = 0 r 1 = 1 (Its multiplicity is 2.) So, by theorem h n = ( n)(1) n = n is a solution. 33
35 Example What is the solution of the recurrence relation a n = 2a n-1 - a n n for n 2, with a 0 =1 and a 1 =2? Solution: a n = b n + h n a n = 4. 2 n n is a solution. Now we should find constants using initial conditions. a 0 = = 1 a 1 = = 2 1 = -3 2 = -3 So, a n = 4. 2 n - 3n
36 Recommended exercises 1,3,15,17,19,21,23,25,31,35 Eric Ruppert s Notes about Solving Recurrences ( 35
Recursive Algorithms. Recursion. Motivating Example Factorial Recall the factorial function. { 1 if n = 1 n! = n (n 1)! if n > 1
Recursion Slides by Christopher M Bourke Instructor: Berthe Y Choueiry Fall 007 Computer Science & Engineering 35 Introduction to Discrete Mathematics Sections 71-7 of Rosen cse35@cseunledu Recursive Algorithms
More informationDiscrete Mathematics: Homework 7 solution. Due: 2011.6.03
EE 2060 Discrete Mathematics spring 2011 Discrete Mathematics: Homework 7 solution Due: 2011.6.03 1. Let a n = 2 n + 5 3 n for n = 0, 1, 2,... (a) (2%) Find a 0, a 1, a 2, a 3 and a 4. (b) (2%) Show that
More informationSystems of Linear Equations
Systems of Linear Equations Beifang Chen Systems of linear equations Linear systems A linear equation in variables x, x,, x n is an equation of the form a x + a x + + a n x n = b, where a, a,, a n and
More informationAssignment 5 - Due Friday March 6
Assignment 5 - Due Friday March 6 (1) Discovering Fibonacci Relationships By experimenting with numerous examples in search of a pattern, determine a simple formula for (F n+1 ) 2 + (F n ) 2 that is, a
More informationSEQUENCES ARITHMETIC SEQUENCES. Examples
SEQUENCES ARITHMETIC SEQUENCES An ordered list of numbers such as: 4, 9, 6, 25, 36 is a sequence. Each number in the sequence is a term. Usually variables with subscripts are used to label terms. For example,
More informationLinear Equations in Linear Algebra
1 Linear Equations in Linear Algebra 1.5 SOLUTION SETS OF LINEAR SYSTEMS HOMOGENEOUS LINEAR SYSTEMS A system of linear equations is said to be homogeneous if it can be written in the form A 0, where A
More information160 CHAPTER 4. VECTOR SPACES
160 CHAPTER 4. VECTOR SPACES 4. Rank and Nullity In this section, we look at relationships between the row space, column space, null space of a matrix and its transpose. We will derive fundamental results
More informationMany algorithms, particularly divide and conquer algorithms, have time complexities which are naturally
Recurrence Relations Many algorithms, particularly divide and conquer algorithms, have time complexities which are naturally modeled by recurrence relations. A recurrence relation is an equation which
More informationMath 55: Discrete Mathematics
Math 55: Discrete Mathematics UC Berkeley, Fall 2011 Homework # 5, due Wednesday, February 22 5.1.4 Let P (n) be the statement that 1 3 + 2 3 + + n 3 = (n(n + 1)/2) 2 for the positive integer n. a) What
More informationMATH 304 Linear Algebra Lecture 18: Rank and nullity of a matrix.
MATH 304 Linear Algebra Lecture 18: Rank and nullity of a matrix. Nullspace Let A = (a ij ) be an m n matrix. Definition. The nullspace of the matrix A, denoted N(A), is the set of all n-dimensional column
More informationMath 55: Discrete Mathematics
Math 55: Discrete Mathematics UC Berkeley, Spring 2012 Homework # 9, due Wednesday, April 11 8.1.5 How many ways are there to pay a bill of 17 pesos using a currency with coins of values of 1 peso, 2 pesos,
More informationCore Maths C1. Revision Notes
Core Maths C Revision Notes November 0 Core Maths C Algebra... Indices... Rules of indices... Surds... 4 Simplifying surds... 4 Rationalising the denominator... 4 Quadratic functions... 4 Completing the
More informationOn closed-form solutions to a class of ordinary differential equations
International Journal of Advanced Mathematical Sciences, 2 (1 (2014 57-70 c Science Publishing Corporation www.sciencepubco.com/index.php/ijams doi: 10.14419/ijams.v2i1.1556 Research Paper On closed-form
More informationLecture 4: Partitioned Matrices and Determinants
Lecture 4: Partitioned Matrices and Determinants 1 Elementary row operations Recall the elementary operations on the rows of a matrix, equivalent to premultiplying by an elementary matrix E: (1) multiplying
More informationTAKE-AWAY GAMES. ALLEN J. SCHWENK California Institute of Technology, Pasadena, California INTRODUCTION
TAKE-AWAY GAMES ALLEN J. SCHWENK California Institute of Technology, Pasadena, California L INTRODUCTION Several games of Tf take-away?f have become popular. The purpose of this paper is to determine the
More informationHOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!
Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following
More informationthe recursion-tree method
the recursion- method recurrence into a 1 recurrence into a 2 MCS 360 Lecture 39 Introduction to Data Structures Jan Verschelde, 22 November 2010 recurrence into a The for consists of two steps: 1 Guess
More information10.2 ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS. The Jacobi Method
578 CHAPTER 1 NUMERICAL METHODS 1. ITERATIVE METHODS FOR SOLVING LINEAR SYSTEMS As a numerical technique, Gaussian elimination is rather unusual because it is direct. That is, a solution is obtained after
More informationa 11 x 1 + a 12 x 2 + + a 1n x n = b 1 a 21 x 1 + a 22 x 2 + + a 2n x n = b 2.
Chapter 1 LINEAR EQUATIONS 1.1 Introduction to linear equations A linear equation in n unknowns x 1, x,, x n is an equation of the form a 1 x 1 + a x + + a n x n = b, where a 1, a,..., a n, b are given
More informationCollatz Sequence. Fibbonacci Sequence. n is even; Recurrence Relation: a n+1 = a n + a n 1.
Fibonacci Roulette In this game you will be constructing a recurrence relation, that is, a sequence of numbers where you find the next number by looking at the previous numbers in the sequence. Your job
More informationON THE EMBEDDING OF BIRKHOFF-WITT RINGS IN QUOTIENT FIELDS
ON THE EMBEDDING OF BIRKHOFF-WITT RINGS IN QUOTIENT FIELDS DOV TAMARI 1. Introduction and general idea. In this note a natural problem arising in connection with so-called Birkhoff-Witt algebras of Lie
More informationMethods for Finding Bases
Methods for Finding Bases Bases for the subspaces of a matrix Row-reduction methods can be used to find bases. Let us now look at an example illustrating how to obtain bases for the row space, null space,
More informationMathematics for Algorithm and System Analysis
Mathematics for Algorithm and System Analysis for students of computer and computational science Edward A. Bender S. Gill Williamson c Edward A. Bender & S. Gill Williamson 2005. All rights reserved. Preface
More informationSOME PROPERTIES OF SYMBOL ALGEBRAS OF DEGREE THREE
SOME PROPERTIES OF SYMBOL ALGEBRAS OF DEGREE THREE CRISTINA FLAUT and DIANA SAVIN Communicated by the former editorial board In this paper, we study some properties of the matrix representations of the
More informationCatalan Numbers. Thomas A. Dowling, Department of Mathematics, Ohio State Uni- versity.
7 Catalan Numbers Thomas A. Dowling, Department of Mathematics, Ohio State Uni- Author: versity. Prerequisites: The prerequisites for this chapter are recursive definitions, basic counting principles,
More informationCS473 - Algorithms I
CS473 - Algorithms I Lecture 4 The Divide-and-Conquer Design Paradigm View in slide-show mode 1 Reminder: Merge Sort Input array A sort this half sort this half Divide Conquer merge two sorted halves Combine
More informationUndergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics
Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights
More informationMetric Spaces. Chapter 7. 7.1. Metrics
Chapter 7 Metric Spaces A metric space is a set X that has a notion of the distance d(x, y) between every pair of points x, y X. The purpose of this chapter is to introduce metric spaces and give some
More informationAppendix: Solving Recurrences [Fa 10] Wil Wheaton: Embrace the dark side! Sheldon: That s not even from your franchise!
Change is certain. Peace is followed by disturbances; departure of evil men by their return. Such recurrences should not constitute occasions for sadness but realities for awareness, so that one may be
More informationNonhomogeneous Linear Equations
Nonhomogeneous Linear Equations In this section we learn how to solve second-order nonhomogeneous linear differential equations with constant coefficients, that is, equations of the form ay by cy G x where
More informationBenford s Law: Tables of Logarithms, Tax Cheats, and The Leading Digit Phenomenon
Benford s Law: Tables of Logarithms, Tax Cheats, and The Leading Digit Phenomenon Michelle Manes (mmanes@math.hawaii.edu) 9 September, 2008 History (1881) Simon Newcomb publishes Note on the frequency
More information1. First-order Ordinary Differential Equations
Advanced Engineering Mathematics 1. First-order ODEs 1 1. First-order Ordinary Differential Equations 1.1 Basic concept and ideas 1.2 Geometrical meaning of direction fields 1.3 Separable differential
More informationMATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set.
MATH 304 Linear Algebra Lecture 9: Subspaces of vector spaces (continued). Span. Spanning set. Vector space A vector space is a set V equipped with two operations, addition V V (x,y) x + y V and scalar
More information6.042/18.062J Mathematics for Computer Science December 12, 2006 Tom Leighton and Ronitt Rubinfeld. Random Walks
6.042/8.062J Mathematics for Comuter Science December 2, 2006 Tom Leighton and Ronitt Rubinfeld Lecture Notes Random Walks Gambler s Ruin Today we re going to talk about one-dimensional random walks. In
More informationMath 115 Spring 2011 Written Homework 5 Solutions
. Evaluate each series. a) 4 7 0... 55 Math 5 Spring 0 Written Homework 5 Solutions Solution: We note that the associated sequence, 4, 7, 0,..., 55 appears to be an arithmetic sequence. If the sequence
More informationNotes on Determinant
ENGG2012B Advanced Engineering Mathematics Notes on Determinant Lecturer: Kenneth Shum Lecture 9-18/02/2013 The determinant of a system of linear equations determines whether the solution is unique, without
More informationSECTION 10-5 Multiplication Principle, Permutations, and Combinations
10-5 Multiplication Principle, Permutations, and Combinations 761 54. Can you guess what the next two rows in Pascal s triangle, shown at right, are? Compare the numbers in the triangle with the binomial
More informationMATRIX ALGEBRA AND SYSTEMS OF EQUATIONS
MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a
More informationLecture 5 Principal Minors and the Hessian
Lecture 5 Principal Minors and the Hessian Eivind Eriksen BI Norwegian School of Management Department of Economics October 01, 2010 Eivind Eriksen (BI Dept of Economics) Lecture 5 Principal Minors and
More informationSolving Systems of Linear Equations Using Matrices
Solving Systems of Linear Equations Using Matrices What is a Matrix? A matrix is a compact grid or array of numbers. It can be created from a system of equations and used to solve the system of equations.
More informationPUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.
PUTNAM TRAINING POLYNOMIALS (Last updated: November 17, 2015) Remark. This is a list of exercises on polynomials. Miguel A. Lerma Exercises 1. Find a polynomial with integral coefficients whose zeros include
More informationContinued Fractions and the Euclidean Algorithm
Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction
More informationGröbner Bases and their Applications
Gröbner Bases and their Applications Kaitlyn Moran July 30, 2008 1 Introduction We know from the Hilbert Basis Theorem that any ideal in a polynomial ring over a field is finitely generated [3]. However,
More informationTaylor and Maclaurin Series
Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions
More informationRandomized algorithms
Randomized algorithms March 10, 2005 1 What are randomized algorithms? Algorithms which use random numbers to make decisions during the executions of the algorithm. Why would we want to do this?? Deterministic
More information4/1/2017. PS. Sequences and Series FROM 9.2 AND 9.3 IN THE BOOK AS WELL AS FROM OTHER SOURCES. TODAY IS NATIONAL MANATEE APPRECIATION DAY
PS. Sequences and Series FROM 9.2 AND 9.3 IN THE BOOK AS WELL AS FROM OTHER SOURCES. TODAY IS NATIONAL MANATEE APPRECIATION DAY 1 Oh the things you should learn How to recognize and write arithmetic sequences
More informationMathematical Induction. Lecture 10-11
Mathematical Induction Lecture 10-11 Menu Mathematical Induction Strong Induction Recursive Definitions Structural Induction Climbing an Infinite Ladder Suppose we have an infinite ladder: 1. We can reach
More informationOn continued fractions of the square root of prime numbers
On continued fractions of the square root of prime numbers Alexandra Ioana Gliga March 17, 2006 Nota Bene: Conjecture 5.2 of the numerical results at the end of this paper was not correctly derived from
More informationMATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 2. x n. a 11 a 12 a 1n b 1 a 21 a 22 a 2n b 2 a 31 a 32 a 3n b 3. a m1 a m2 a mn b m
MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS 1. SYSTEMS OF EQUATIONS AND MATRICES 1.1. Representation of a linear system. The general system of m equations in n unknowns can be written a 11 x 1 + a 12 x 2 +
More information4.5 Linear Dependence and Linear Independence
4.5 Linear Dependence and Linear Independence 267 32. {v 1, v 2 }, where v 1, v 2 are collinear vectors in R 3. 33. Prove that if S and S are subsets of a vector space V such that S is a subset of S, then
More information( ) which must be a vector
MATH 37 Linear Transformations from Rn to Rm Dr. Neal, WKU Let T : R n R m be a function which maps vectors from R n to R m. Then T is called a linear transformation if the following two properties are
More information9.2 Summation Notation
9. Summation Notation 66 9. Summation Notation In the previous section, we introduced sequences and now we shall present notation and theorems concerning the sum of terms of a sequence. We begin with a
More informationInner Product Spaces
Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and
More informationSubspaces of R n LECTURE 7. 1. Subspaces
LECTURE 7 Subspaces of R n Subspaces Definition 7 A subset W of R n is said to be closed under vector addition if for all u, v W, u + v is also in W If rv is in W for all vectors v W and all scalars r
More informationPhantom bonuses. November 22, 2004
Phantom bonuses November 22, 2004 1 Introduction The game is defined by a list of payouts u 1, u 2,..., u l, and a list of probabilities p 1, p 2,..., p l, p i = 1. We allow u i to be rational numbers,
More informationAnswer: (a) Since we cannot repeat men on the committee, and the order we select them in does not matter, ( )
1. (Chapter 1 supplementary, problem 7): There are 12 men at a dance. (a) In how many ways can eight of them be selected to form a cleanup crew? (b) How many ways are there to pair off eight women at the
More informationLinear Algebra I. Ronald van Luijk, 2012
Linear Algebra I Ronald van Luijk, 2012 With many parts from Linear Algebra I by Michael Stoll, 2007 Contents 1. Vector spaces 3 1.1. Examples 3 1.2. Fields 4 1.3. The field of complex numbers. 6 1.4.
More informationThe Chinese Remainder Theorem
The Chinese Remainder Theorem Evan Chen evanchen@mit.edu February 3, 2015 The Chinese Remainder Theorem is a theorem only in that it is useful and requires proof. When you ask a capable 15-year-old why
More informationQuotient Rings and Field Extensions
Chapter 5 Quotient Rings and Field Extensions In this chapter we describe a method for producing field extension of a given field. If F is a field, then a field extension is a field K that contains F.
More informationHandout NUMBER THEORY
Handout of NUMBER THEORY by Kus Prihantoso Krisnawan MATHEMATICS DEPARTMENT FACULTY OF MATHEMATICS AND NATURAL SCIENCES YOGYAKARTA STATE UNIVERSITY 2012 Contents Contents i 1 Some Preliminary Considerations
More informationSECTION 10-2 Mathematical Induction
73 0 Sequences and Series 6. Approximate e 0. using the first five terms of the series. Compare this approximation with your calculator evaluation of e 0.. 6. Approximate e 0.5 using the first five terms
More informationIntroduction to Time Series Analysis. Lecture 6.
Introduction to Time Series Analysis. Lecture 6. Peter Bartlett www.stat.berkeley.edu/ bartlett/courses/153-fall2010 Last lecture: 1. Causality 2. Invertibility 3. AR(p) models 4. ARMA(p,q) models 1 Introduction
More informationZero: If P is a polynomial and if c is a number such that P (c) = 0 then c is a zero of P.
MATH 11011 FINDING REAL ZEROS KSU OF A POLYNOMIAL Definitions: Polynomial: is a function of the form P (x) = a n x n + a n 1 x n 1 + + a x + a 1 x + a 0. The numbers a n, a n 1,..., a 1, a 0 are called
More information3.2 Roulette and Markov Chains
238 CHAPTER 3. DISCRETE DYNAMICAL SYSTEMS WITH MANY VARIABLES 3.2 Roulette and Markov Chains In this section we will be discussing an application of systems of recursion equations called Markov Chains.
More informationSo far, we have looked at homogeneous equations
Chapter 3.6: equations Non-homogeneous So far, we have looked at homogeneous equations L[y] = y + p(t)y + q(t)y = 0. Homogeneous means that the right side is zero. Linear homogeneous equations satisfy
More informationCreating, Solving, and Graphing Systems of Linear Equations and Linear Inequalities
Algebra 1, Quarter 2, Unit 2.1 Creating, Solving, and Graphing Systems of Linear Equations and Linear Inequalities Overview Number of instructional days: 15 (1 day = 45 60 minutes) Content to be learned
More informationLecture 14: Section 3.3
Lecture 14: Section 3.3 Shuanglin Shao October 23, 2013 Definition. Two nonzero vectors u and v in R n are said to be orthogonal (or perpendicular) if u v = 0. We will also agree that the zero vector in
More informationThese axioms must hold for all vectors ū, v, and w in V and all scalars c and d.
DEFINITION: A vector space is a nonempty set V of objects, called vectors, on which are defined two operations, called addition and multiplication by scalars (real numbers), subject to the following axioms
More informationMATH2210 Notebook 1 Fall Semester 2016/2017. 1 MATH2210 Notebook 1 3. 1.1 Solving Systems of Linear Equations... 3
MATH0 Notebook Fall Semester 06/07 prepared by Professor Jenny Baglivo c Copyright 009 07 by Jenny A. Baglivo. All Rights Reserved. Contents MATH0 Notebook 3. Solving Systems of Linear Equations........................
More informationReduced echelon form: Add the following conditions to conditions 1, 2, and 3 above:
Section 1.2: Row Reduction and Echelon Forms Echelon form (or row echelon form): 1. All nonzero rows are above any rows of all zeros. 2. Each leading entry (i.e. left most nonzero entry) of a row is in
More information1.2. Successive Differences
1. An Application of Inductive Reasoning: Number Patterns In the previous section we introduced inductive reasoning, and we showed how it can be applied in predicting what comes next in a list of numbers
More information2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system
1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables
More informationSecond Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.
Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard
More informationExtrinsic geometric flows
On joint work with Vladimir Rovenski from Haifa Paweł Walczak Uniwersytet Łódzki CRM, Bellaterra, July 16, 2010 Setting Throughout this talk: (M, F, g 0 ) is a (compact, complete, any) foliated, Riemannian
More informationTHE DIMENSION OF A VECTOR SPACE
THE DIMENSION OF A VECTOR SPACE KEITH CONRAD This handout is a supplementary discussion leading up to the definition of dimension and some of its basic properties. Let V be a vector space over a field
More informationThis unit will lay the groundwork for later units where the students will extend this knowledge to quadratic and exponential functions.
Algebra I Overview View unit yearlong overview here Many of the concepts presented in Algebra I are progressions of concepts that were introduced in grades 6 through 8. The content presented in this course
More informationGod created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886)
Chapter 2 Numbers God created the integers and the rest is the work of man. (Leopold Kronecker, in an after-dinner speech at a conference, Berlin, 1886) God created the integers and the rest is the work
More informationStanford Math Circle: Sunday, May 9, 2010 Square-Triangular Numbers, Pell s Equation, and Continued Fractions
Stanford Math Circle: Sunday, May 9, 00 Square-Triangular Numbers, Pell s Equation, and Continued Fractions Recall that triangular numbers are numbers of the form T m = numbers that can be arranged in
More informationSome facts about polynomials modulo m (Full proof of the Fingerprinting Theorem)
Some facts about polynomials modulo m (Full proof of the Fingerprinting Theorem) In order to understand the details of the Fingerprinting Theorem on fingerprints of different texts from Chapter 19 of the
More informationLS.6 Solution Matrices
LS.6 Solution Matrices In the literature, solutions to linear systems often are expressed using square matrices rather than vectors. You need to get used to the terminology. As before, we state the definitions
More informationCOWLEY COLLEGE & Area Vocational Technical School
COWLEY COLLEGE & Area Vocational Technical School COURSE PROCEDURE FOR DIFFERENTIAL EQUATIONS MTH 4465 3 Credit Hours Student Level: This course is open to students on the college level in the sophomore
More informationInner product. Definition of inner product
Math 20F Linear Algebra Lecture 25 1 Inner product Review: Definition of inner product. Slide 1 Norm and distance. Orthogonal vectors. Orthogonal complement. Orthogonal basis. Definition of inner product
More informationLinear Programming I
Linear Programming I November 30, 2003 1 Introduction In the VCR/guns/nuclear bombs/napkins/star wars/professors/butter/mice problem, the benevolent dictator, Bigus Piguinus, of south Antarctica penguins
More informationTriangle deletion. Ernie Croot. February 3, 2010
Triangle deletion Ernie Croot February 3, 2010 1 Introduction The purpose of this note is to give an intuitive outline of the triangle deletion theorem of Ruzsa and Szemerédi, which says that if G = (V,
More informationCircles in Triangles. This problem gives you the chance to: use algebra to explore a geometric situation
Circles in Triangles This problem gives you the chance to: use algebra to explore a geometric situation A This diagram shows a circle that just touches the sides of a right triangle whose sides are 3 units,
More information1 VECTOR SPACES AND SUBSPACES
1 VECTOR SPACES AND SUBSPACES What is a vector? Many are familiar with the concept of a vector as: Something which has magnitude and direction. an ordered pair or triple. a description for quantities such
More informationSMT 2014 Algebra Test Solutions February 15, 2014
1. Alice and Bob are painting a house. If Alice and Bob do not take any breaks, they will finish painting the house in 20 hours. If, however, Bob stops painting once the house is half-finished, then the
More informationDIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents
DIFFERENTIABILITY OF COMPLEX FUNCTIONS Contents 1. Limit definition of a derivative 1 2. Holomorphic functions, the Cauchy-Riemann equations 3 3. Differentiability of real functions 5 4. A sufficient condition
More information1.2 Solving a System of Linear Equations
1.. SOLVING A SYSTEM OF LINEAR EQUATIONS 1. Solving a System of Linear Equations 1..1 Simple Systems - Basic De nitions As noticed above, the general form of a linear system of m equations in n variables
More informationZeros of a Polynomial Function
Zeros of a Polynomial Function An important consequence of the Factor Theorem is that finding the zeros of a polynomial is really the same thing as factoring it into linear factors. In this section we
More informationSecond-Order Linear Differential Equations
Second-Order Linear Differential Equations A second-order linear differential equation has the form 1 Px d 2 y dx 2 dy Qx dx Rxy Gx where P, Q, R, and G are continuous functions. We saw in Section 7.1
More informationProbability Generating Functions
page 39 Chapter 3 Probability Generating Functions 3 Preamble: Generating Functions Generating functions are widely used in mathematics, and play an important role in probability theory Consider a sequence
More informationLinear Algebra Notes
Linear Algebra Notes Chapter 19 KERNEL AND IMAGE OF A MATRIX Take an n m matrix a 11 a 12 a 1m a 21 a 22 a 2m a n1 a n2 a nm and think of it as a function A : R m R n The kernel of A is defined as Note
More informationLinearly Independent Sets and Linearly Dependent Sets
These notes closely follow the presentation of the material given in David C. Lay s textbook Linear Algebra and its Applications (3rd edition). These notes are intended primarily for in-class presentation
More informationNOTES ON LINEAR TRANSFORMATIONS
NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all
More informationRefined enumerations of alternating sign matrices. Ilse Fischer. Universität Wien
Refined enumerations of alternating sign matrices Ilse Fischer Universität Wien 1 Central question Which enumeration problems have a solution in terms of a closed formula that (for instance) only involves
More informationMA106 Linear Algebra lecture notes
MA106 Linear Algebra lecture notes Lecturers: Martin Bright and Daan Krammer Warwick, January 2011 Contents 1 Number systems and fields 3 1.1 Axioms for number systems......................... 3 2 Vector
More informationMatrix-Chain Multiplication
Matrix-Chain Multiplication Let A be an n by m matrix, let B be an m by p matrix, then C = AB is an n by p matrix. C = AB can be computed in O(nmp) time, using traditional matrix multiplication. Suppose
More information3. Mathematical Induction
3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)
More informationPolynomial Invariants
Polynomial Invariants Dylan Wilson October 9, 2014 (1) Today we will be interested in the following Question 1.1. What are all the possible polynomials in two variables f(x, y) such that f(x, y) = f(y,
More information