S. Tanny MAT 344 Spring 1999. be the minimum number of moves required.



Similar documents
Soving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE The absolute value of the complex number z a bi is

2-3 The Remainder and Factor Theorems

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER?

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

Basic Elements of Arithmetic Sequences and Series

Infinite Sequences and Series

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

Sequences and Series

CS103X: Discrete Structures Homework 4 Solutions

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

Section 8.3 : De Moivre s Theorem and Applications

where: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return

Factoring x n 1: cyclotomic and Aurifeuillian polynomials Paul Garrett <garrett@math.umn.edu>

Heat (or Diffusion) equation in 1D*

1. MATHEMATICAL INDUCTION

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized?

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed.

NATIONAL SENIOR CERTIFICATE GRADE 11

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here).

A probabilistic proof of a binomial identity

CHAPTER 11 Financial mathematics

7.1 Finding Rational Solutions of Polynomial Equations

Determining the sample size

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Section 11.3: The Integral Test

Theorems About Power Series

3. Greatest Common Divisor - Least Common Multiple

Asymptotic Growth of Functions

A Recursive Formula for Moments of a Binomial Distribution

5.3. Generalized Permutations and Combinations

SEQUENCES AND SERIES

Output Analysis (2, Chapters 10 &11 Law)

Question 2: How is a loan amortized?

Chapter 7 Methods of Finding Estimators

Hypothesis testing. Null and alternative hypotheses

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n

Chapter 7: Confidence Interval and Sample Size

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

Math 114- Intermediate Algebra Integral Exponents & Fractional Exponents (10 )

Properties of MLE: consistency, asymptotic normality. Fisher information.

CHAPTER 3 THE TIME VALUE OF MONEY

AP Calculus AB 2006 Scoring Guidelines Form B

Solving Logarithms and Exponential Equations

Convexity, Inequalities, and Norms

BENEFIT-COST ANALYSIS Financial and Economic Appraisal using Spreadsheets

Solutions to Exercises Chapter 4: Recurrence relations and generating functions

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4

NATIONAL SENIOR CERTIFICATE GRADE 11

Lesson 15 ANOVA (analysis of variance)

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009)

1 Computing the Standard Deviation of Sample Means

hp calculators HP 12C Statistics - average and standard deviation Average and standard deviation concepts HP12C average and standard deviation

INFINITE SERIES KEITH CONRAD

Maximum Likelihood Estimators.

I. Chi-squared Distributions

Annuities Under Random Rates of Interest II By Abraham Zaks. Technion I.I.T. Haifa ISRAEL and Haifa University Haifa ISRAEL.

1 Correlation and Regression Analysis

MATH 083 Final Exam Review

REVIEW OF INTEGRATION

SEQUENCES AND SERIES CHAPTER

3. If x and y are real numbers, what is the simplified radical form

NEW HIGH PERFORMANCE COMPUTATIONAL METHODS FOR MORTGAGES AND ANNUITIES. Yuri Shestopaloff,

Solutions to Selected Problems In: Pattern Classification by Duda, Hart, Stork

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Elementary Theory of Russian Roulette

Overview of some probability distributions.


Inference on Proportion. Chapter 8 Tests of Statistical Hypotheses. Sampling Distribution of Sample Proportion. Confidence Interval

Escola Federal de Engenharia de Itajubá

Project Deliverables. CS 361, Lecture 28. Outline. Project Deliverables. Administrative. Project Comments

GCSE STATISTICS. 4) How to calculate the range: The difference between the biggest number and the smallest number.

CHAPTER 7: Central Limit Theorem: CLT for Averages (Means)

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

BINOMIAL EXPANSIONS In this section. Some Examples. Obtaining the Coefficients

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8

Listing terms of a finite sequence List all of the terms of each finite sequence. a) a n n 2 for 1 n 5 1 b) a n for 1 n 4 n 2

Permutations, the Parity Theorem, and Determinants

4.3. The Integral and Comparison Tests

THE LEAST COMMON MULTIPLE OF A QUADRATIC SEQUENCE

NATIONAL SENIOR CERTIFICATE GRADE 12

Learning objectives. Duc K. Nguyen - Corporate Finance 21/10/2014

Class Meeting # 16: The Fourier Transform on R n

THE HEIGHT OF q-binary SEARCH TREES

The following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles

Incremental calculation of weighted mean and variance

5: Introduction to Estimation

Sampling Distribution And Central Limit Theorem

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals

Vladimir N. Burkov, Dmitri A. Novikov MODELS AND METHODS OF MULTIPROJECTS MANAGEMENT

Finding the circle that best fits a set of points

Descriptive Statistics

CURIOUS MATHEMATICS FOR FUN AND JOY

Confidence Intervals for One Mean

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method

LECTURE 13: Cross-validation

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006

Transcription:

S. Tay MAT 344 Sprig 999 Recurrece Relatios Tower of Haoi Let T be the miimum umber of moves required. T 0 = 0, T = 7 Iitial Coditios * T = T + $ T is a sequece (f. o itegers). Solve for T? * is a recurrece, differece equatio (liear, ohomogeeous, costat coefficiet) Set U 0 = T 0 +, U = T + $ The U = T + = T + + = (T + ) so U = U = U = ÿ = U = ˆ T = Suppose a + = a +, a 0 = Let U = a +, U 0 = The U + = a + + ( + ) = a + + ( + ) = (a + ) + = U + Thus, U is like the T i the precedig example, except U 0 = while T 0 = 0. I fact, sice T =, the {U } is just {T } advaced oe step, i.e. U = T + = + ˆ a = + = + ( + ) Notice how the solutio of oe recurrece ofte ca be reduced to the solutio of a simpler oe. 7

S. Tay MAT 344 Sprig 999 Suppose the recursio were L = L +, L 0 = The we ca expad out as follows: L = L + ( ) + = L 3 + ( ) + ( ) + = = L 0 + + + þ + = + (%) This describes the umber of regios formed by itersectig lies i the plae, o parallel ad o 3 itersect i a poit (PIZZA CUTTING PROBLEM). Geeral Problem (*) F(Y + k,y + k, þ, Y ) = 0 Differece equatio of order k(dfe) Assume F liear, costat coefficiets (**) Y + k + a Y + k + þ + a k Y () = 0 If () = 0, Homogeeous; otherwise ohomo. Note the strog aalogy with D.E.! Suppose that Y = S () is a solutio. The S ( + k) + a S ( + k ) + þ + a k S () ()=0 If S () is ay other solutio, the [S ( + k) S ( + k)] + a [S ( + k ) S (+ k )] + ÿ + a k [S () S ()] = 0 It follows that S () S () is a solutio of the Homogeeous equatio related to (**) (obtaied by (igorig ()). What is the Geeral Solutio of a DFE? It s a family of fuctios, usually characterized by a parameter(s) which ca take o differet values. 73

S. Tay MAT 344 Sprig 999 From the above, the geeral solutio for (**) is just the geeral solutio to the related HOMO equatio plus ay particular solutio to the NONHOMO equatio (**), i.e. S NH () = S H () + S p () where S p () is ay solutio of (**), S H () is geeral solutio of related HOMO ad S NH () is geeral solutio of (**) Solvig HOMO (i) First Order DFE Suppose Y + + a Y = 0 (k = ) The Y + = a Y = () a Y = ÿ = () a Y = (a ) + Y 0 where Y 0 is a arbitrary umber (iitial value of sequece). CHECK: (a ) + Y 0 + a (a ) Y 0 = a (a ) Y 0 + a (a ) Y 0 = 0 (ii) Higher Order DFE Notice that if U () ad U () are both solutios of the homo equatio (H) Y +k + a Y + k + ÿ + a k Y = 0 the so is C U () + C U () where C, C 0 ú. Two solutios of (H) are differet iff ò C such that U () = CU () 74

S. Tay MAT 344 Sprig 999 It ca be show that if U (), U (), ÿ, U k () are k differet solutios of (H), the the geeral solutio is Fidig Differet Solutios k S H () = j C i U i () where C i 0 ú. i' Y + + a Y + + a Y = 0 Characteristic polyomial p(8) = 8 + a 8 + a Let p(8) have roots 8 8 (Real 8,8 ). The U () = 8 U () = 8 are differet solutios, sice 8 + + a 8 + + a 8 = 8 (8 + a 8 +a ) = 0 ad the same holds for 8 ad clearly U () CU () for ay C 0 ú. Thus, the geeral solutio is C 8 + C 8 Exercise: F + = F + + F F 0 = F = Geeral Solutio: F + F + F = 0. P(8) = 8 8, roots ± % S H () = C + C & F 0 = S H (0) = Y C + C = % & F = S H () = Y C + C = % ˆ C = C = & 7

S. Tay MAT 344 Sprig 999 % % ˆ F = & % % & Sice > ad <, for large /0 /0 % % F I fact you ca verify that for all, /0 & so that F = iteger earest (Also otice that < 0 so that % % % % < 0. /0 % is alterately above or below F.) F Also, % % P = J Golde Mea F AB AC ' AC CB Suppose the two roots were the same p(8) = (8 8 ) The U () = 8 is oe solutio, we eed a secod. Suppose the secod looks like 8 V() for some V(), the we have V( + ) 8 + 8 V( + ) 8 + + 8 V()8 = 0 Divide by 8 + to get V( + ) V( + ) + V() = 0 76

S. Tay MAT 344 Sprig 999 By ispectio we otice that possible solutios are V() = (!!) ad V() =. This latter solutio for V() gives a secod (differet) solutio to the origial equatio. Thus, the geeral solutio is S H () =C 8 C 8 Exercise: Y + 4Y + + 4Y = 0 = 8 (C + C ) P(8) = 8 48 + 4 = (8 ) Y = (C + C ) The fial possibility is that the roots are distict but ot real. The they must be complex cojugates (sice the coefficiets are real), say " ± i$. The earlier aalysis gives S H () = C (" + i$) + C (" i$) (sice we ever used the fact that the roots were real explicitly!). What s wrog? NOTHING, except the solutio S H (), may ot be real. We wat real solutio for practical problems. What to do? Recall: " + i$ = r[cos + i si] where r = " %$ " cos = si = r De Moivre: (" + i$) = r [cos + i si ] $ r Thus. {(" + i$) + (" i$) } = r cos (" i$) = r [cos i si ] {(" + i$) (" i$) } = r si i Thus, r cos ad r si are diff. real solutios. Geeral Solutio S H () = c r cos + c r si 77

S. Tay MAT 344 Sprig 999 Example: Y + = (Y + + Y ) r ' 4 % 3 4 p(8) = 8 + 8 +, roots & ± i 3 ', cos ' &, si ' 3 B so = ˆ Y = c cos B 3 3 % c si B 3 Next Step: Geeral for ay k. This is relatively easy: ) if all the k roots are real ad distict, say, 8,8, ÿ, 8 k the geeral solutio is S H () = j k i' ) if 8 i occurs with multiplicity m i, the distict solutios associated with it are Do this for all k roots c i 8 i 8 i,8 i, 8 i,ÿ,m& 8 i i 3) wheever a root is complex, its cojugate must also be a root (coeff of polyomial are real!) [Recall that ay polyomial p(8) ca be writte as a product of liear ad quadratic factors.] Use the approach described above for this pair of complex cojugate roots. Exercise Y + 3 Y + + Y + Y = 0 p(8) = 8 3 8 + 8 = (8 )(8 + ) roots are, ± i, r =, = B Y = c + c cos B % c si B 3 Exercise H + 3 H + H = 0, H 0 = H = H = Fid a eat formula for H. What about for the recursio: G + 3 G + + G = 0, G 0 = G = G = 78

S. Tay MAT 344 Sprig 999 Try to geeralize these results for : H + k + = H + k + H, H 0 = H = ÿ = H k = G + k + = G + k G, G 0 = G = ÿ = G k = NoHomogeeous Equatios C o geeral solutio, eve i case of costat coefficiets C some special cases ca be solved, whe the fuctio o the RHS is of a certai type, amely, () = polyomial i, e.g. + () = expoomial i, e.g. 3 () = (poly.) (exp.), e.g. @ C may other special cases ca also be solved, but we do t wat to get ito this (for those iterested, see Kelley ad Peterse, Differece Equatios, Academic Press (99)) Exercise Y + Y = Let s first fid oe particular solutio. Clearly Y is ot a costat fuctio (sice the Y + Y = 0 œ). Let s try Y = b + b 0, a liear polyomial Y + Y = [b ( + ) + b 0 ] [b + b 0 ] = b Thus, b =, while b 0 is arbitrary. But recall that the solutio (geeral) to the homogeeous related equatio is just a costat K. Thus, the geeral solutio to () is CHECK: Y + Y = K + ( + ) (K + ) = Y = K + Exercise Y + Y = 3 + The solutio to the related homogeeous equatio Y + Y = 0 is K, where K is determied by the iitial value of this sequece. We eed a particular solutio for the ohomogeeous equatio. Let s try 79

S. Tay MAT 344 Sprig 999 The ˆ 3 + = b + (b b 0 ) ˆ b = 3 b 0 = Y = b 0 + b Y = b 0 + b ( + ) (b 0 + b ) Ȳ = (b0 + b) + (b) CHECK: [3( + ) ] [3 ] = 3 8 + 6 + 0 = 3 +. Exercise 3 Y + + Y = 4 Solutio to the related homo equatio is K(). A particular solutio : try Y = b.4 The Y + + Y = b@4 + + b@4 = b@4 [4 + ] = b4 ˆ 4 = b@4 Y b = CHECK: 4 + + 4 = 4 [4 + ] = 4 Geeral Solutio: Y = 4 + K () Exercise 4 Y + 3Y = ( + 3)@7 solutio to related homo equatio K @ 3 For a particular solutio try: Y = (b 0 + b ) 7 Y + 3Y = [(b 0 + b ( + )]7 + 3[b 0 + b ]7 ˆ ( + 3)7 = (4b 0 + 7b )7 + @4b @7 ˆ 4b = 4b 0 + 7b = 3. ˆ b = b 0 = 4 6 80

S. Tay MAT 344 Sprig 999 CHECK: 6 % 4 ( % ) 7% & 3 6 % 4 7 = 3 6 & 6 % 7 4 7 % 7 4 & 3 4 7 = 3@7 + @7 = ( + 3)7 ˆ Y = K@3 + I geeral, for 6 % 4 7 Y + + ay = P m () s where P m () is a pol. of degree m, a ohomo solutio is give by Y = Q m ()s s a Y = Q m ()s s = a ad the coefficiets of the pol. Q m () (of deg m) ca be determied by subst. Ȳ ito above equatio (method of udetermied coeff.) For Y + + a Y + + a Y = P m () s we ca show that a particular solutio is Y = Q m ()s, s 8,8 Y = Q m ()s, s = 8, 8 Y = Q m ()s, s = 8 =8 where 8,8 are the roots of the characteristic pol. of the related HOMO equatio. Exercise Y + + Y + +Y = ( + 3) 8

S. Tay MAT 344 Sprig 999 Here P m () = + 3, s = ad the ch. pol. is 8 + 8 +, with roots 8 = 8 =. Thus, a particular solutio has form Y = (" 0 + " ) Solve for " 0, " by substitutio. [" 0 + " ( + )] + + [" 0 + " ( + )] + + (" 0 + " ) =( + 3) Y4(" 0 + " + " ) + 4(" 0 + " + " ) + " 0 + " = + 3 Y9" 0 + " = 3, 9" = ˆ" =, " 0 = 9 Exercise 7 Y + + Y + + Y = " Here P m () =, s = ", roots of characteristic polyomial 8 + 8 + are. A particular & ± i 3 solutio has form c". Substitutio yields c" + + c" + + c" = " Assume " 0. The c" + c" + c = or c(" + " + ) =. If " ot a root of the ch. Pol. the c = " % " %. Sice the roots of the ch. pol. are complex, if " 0 ú we kow that " is ot a root so we re doe. Exercise 3. Like Exercise above. Try Y + + Y + + Y = () Y = c () () + c ( + ) + () + c( + ) + () c = () c[ + 4 + 4 4 + ] = () c ˆ c = Y c = 8