CALCULATION OF FIBONACCI VECTORS

Size: px
Start display at page:

Download "CALCULATION OF FIBONACCI VECTORS"

Transcription

1 CALCULATION OF FIBONACCI VECTORS Stuart D. Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA ad Dai Novak Departmet of Mathematics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA Draft of 2008 May 19 ABSTRACT 1

2 1. INTRODUCTION This chapter shows how to calculate ay Fiboacci vector directly, orecursively, geeralizig Biet s formula for the origial Fiboacci sequece. Let be the dimesio of the vector space. 2. SECTION 2 Let F represet the sequece of Fiboacci vectors of dimesio. Let F k represet the Fiboacci vector of idex k, the vector that is displaced by k steps i the sequece from the seed vector F 0. To move oe step from a give vector F k to the ext vector F k + 1 i the sequece is accomplished by applyig the -dimesioal Fiboacci vector sequece augmetatio matrix Q. F T k + 1 Q F T k 1 The superscript T attached to the symbol of a vector or matrix idicates the traspose of that etity. Because we usually defie vectors without such a superscript to represet row vectors, for example F k, the symbol of a vector with a T superscript represets a colum vector, for example F T k. I this recursive defiitio of a Fiboacci vector sequece, the augmetatio matrix Q trasforms the give vector ito the ext vector Q The elemets of the augmetatio matrix are represeted by Q i, j, where 1 i is the row idex ad 1 j is the colum idex. 0 i + j Q i, j 1 i + j > The effect or the applicatio of the augmetatio matrix is to make the ith compoet of the ext vector equal to the sum of the last i + 1 compoets of the give vector. Note that, sice the augmetatio matrix is a symmetric matrix, Q T Q, we ca write equatio 1 without superscript T s. 3 F k + 1 F k Q 4 The recursive defiitio of the sequece is ot eough, however. We also eed to specify a startig poit, the seed vector of the sequece. For a Fiboacci vector sequece, we specify the followig seed vector F 0. F

3 All but the last compoet of the seed vector are zeros; the last compoet is a oe. 0 1 j < F 0, j 1 j 6 Note that we could have specified a differet seed vector, either trivially by specifyig a differet vector i the same sequece, or sigificatly by specifyig a vector ot i this sequece ad geeratig a o-fiboacci vector sequece. But we shall restrict our attetio here to Fiboacci sequeces grow from the specified seed vectors. The set of the first Fiboacci vectors F k for 0 k 1 forms the the seed matrix F 0 1. F 0 F 0 F 1 1. F 1 F 0 F 0 Q. F 0 Q 1 The kth row of the seed matrix is the Fiboacci vector of idex k 1, F k 1. 7 F 0 1 k F k 1 F 0 Q k 1 8 The characteristic polyomial of degree i the variable x is D x, D x Q xi 9 where the pair of vertical lies extracts the determiat of the eclosed matrix ad I is the by idetity matrix. It may be expressed explicitly as a polyomial, a power series of degree i the variable x. D x d jx j 10 j0 I aother chapter, we determie the values of the coefficiets d j. This polyomial has roots x i for 1 i. The polyomial may also be writte i terms of these roots. D x 1 i1 x x i 11 The roots of the characteristic polyomial are real ad distict, so that they may be ordered. We will place the roots i ascedig order, so that i < j x i < x j. The ordered set of roots is the root vector x. x x 1 x 2 x It is coveiet to have a otatio for a vector, each compoet of which is a certai power of the same compoet of aother vector. Therefore, defie the jth power of a vector, v j, as the vector the ith compoet of which is the jth power of the ith compoet of the vector v. 12 v j i vi j 13 3

4 Thus, for example, we will write x j i for the ith compoet of the jth power of the vector x, istead of its equivalet expressio x i j for the jth power of the ith compoet of the vector x. The defiig property of the roots of the characteristic polyomial is that, if the variable x is set equal to the value of oe of its roots x i, the characteristic polyomial evaluates to zero. D x i d jx j i 0 14 j0 Let us form arbitrary liear combiatios A k of the kth powers of the roots x i of the characteristic polyomial. A k x k a x k ia i 15 Thik of this as the ier scalar or dot product of x k, the kth power of the -dimesioal root vector x, with a arbitrary -dimesioal colum vector a. Such arbitrary combiatios satisfy the followig relatio. i1 d ja j 0 16 j0 The proof of this relatio 16 follows straightforwardly from the defiitio of the arbitrary combiatios 15 ad the defiig property of the roots of the characteristic polyomial 14 by rearragemet. d ja j j0 d j x j ia i j0 i1 a i d jx j i i0 j0 a id x i 0 17 Now, let us form special liear combiatios of the roots of the characteristic polyomial to represet the compoets of Fiboacci vectors. Form the jth compoet of the kth Fiboacci vector, F k, j as the ier product of x k with a differet -dimesioal colum vector f, j for each compoet. F k, j x k f, j i0 x k if i, j 18 The symbol f represets a matrix, the Fiboacci root power combiatio matrix; f i, j, the elemet i its ith row ad jth colum; f, j, its jth colum vector; ad f i,, its ith row vector. The kth Fiboacci vector is represeted by F k. F k x k f i1 x k if i, 19 We do ot kow the value of the combiatio matrix f, but if we could figure it out, the we would have a procedure for calculatig ay Fiboacci vector, without havig to calculate all the vectors i betwee. i1 Let us represet aew the seed matrix F 0 1, which we defied i 7, by substitutig ito each of its rows this represetatio 19 of each of the first Fiboacci vectors as combiatios of powers of the root 4

5 vector. F 0 F 0 F 1 1. F 1 x 0 f x 1 f. x 1 f 1 x. x 1 Here, the symbol 1 represets the -dimesioal row vector, all of whose elemets are 1 s. f 20 Defie the root matrix X as the matrix whose ith row, X i,, is x i 1, the i 1th power of the root vector x. X i, x i 1 21 Thus, the elemet X i, j of the root matrix X i its ith row ad jth colum is the i 1th power of the jth root of the characteristic polyomial of degree. X i, j x i 1 j 22 Displayed i more detail, the root matrix X appears as follows. x x 1 x x 1 x 2... x X..... x 1 1 x x 1 x 1 Where have you see that matrix before? x 1 23 I equatio 20, you saw that the seed matrix is the product of what you ow recogize as the root matrix X ad the combiatio matrix f. F 0 1 X f 24 We ca fid the combiatio matrix f by multiplyig this equatio by the iverse of the root matrix X 1. f X 1 F 0 1 Now, substitute this ito equatio 19 to fid the kth Fiboacci vector. 25 Fially, we fid that the kth Fiboacci vector is the product of the kth power of the root vector x k, the iverse of the root matrix X 1 ad the seed matrix F 0 1, i that order. F k x k X 1 F 0 1 What we have foud here is a procedure for calculatig ay Fiboacci vector without havig to calculate all the vectors i betwee. To costruct the seed matrix, you do have to calculate the first 1 vectors the seed vector is give. Ad to costruct the root vector ad the root matrix, you do have to determie the roots 26 5

6 x i for 1 i of the characteristic polyomial D x. By cosiderig the followig example, you will see that what we have here i equatio 26 is the geeralizatio to Fiboacci vectors of Biet s formula for calculatig the origial Fiboacci umbers, which are the compoets of the vectors of the two-dimesioal Fiboacci vector sequece F 2. Cosider the case 2. The characteristic polyomial is D 2 x 1 x + x 2. The root vector x 2 is x 2 1, x 2 2, but let us write it as x 1, x 2 for brevity i this case. x 1, x 2 1 φ, φ 1 5, cos α 2, 2 cos α 2 27 where α 2 π 5 is the miimal agle betwee edges sides or diagoals of a regular petago. Now, let us apply the geeral formula 26 for calculatig Fiboacci vectors i dimesios to calculate the kth Fiboacci vector i 2 two dimesios. 1 F 2 k x k 1, x k φ k, φ k 1 1 x 1 x φ φ φ k 1 φ k, φ k 1 1 φ k 1 + φ k 1 φ k F k, F k 1 + F k 2φ 1 F k, F k where F k xk 2 x k 1 φk 1 φ k x 2 x 1 2φ 1 1+ k k cos α 2 k 1 2 cos α 2 k 4 cos α Observe that this is Biet s formula for calculatig the kth Fiboacci umber. Thus, we see that the geeral formula 26 for calculatig Fiboacci vectors i dimesios is the geeralizatio of Biet s formula from 2 two to > 2 higher dimesioal Fiboacci vectors. XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX This chapter will ed here. The followig material o the characteristic polyomial equatio ad its coefficiets will move to aother chapter. 2. FIBONACCI CHARACTERISTIC POLYNOMIALS Juge ad Hoggatt [2] derive formulas for the Fiboacci characteristic polyomials D x. For eve dimesios 2m, the characteristic polyomials are give by their equatio 21. D 2m x [m/2] k0 1 k m k k k0 2x 2 1 m 2k x 4k [m 1/2] m k xx 1 k 2x 2 1 m 2k 1 x 4k 30 k 6

7 For odd dimesios 2m + 1, the polyomials are give by their equatio 22, which, whe corrected, reads as follows. [m/2] m k D 2m+1 x 1 x 1 k 2x 2 1 m 2k x 4k k k0 [m 1/2] +x 3 k0 m k 1 1 k 2x 2 1 m 2k 1 x 4k 31 k We shall say that these formulas express the polyomials implicitly, ot explicitly, as a power series i x, which we will do later. Note that the latter equatio is derived from Juge ad Hoggatt s equatio 14, which, whe corrected, reads as follows. 1 x + x 3 t 1 2x 2 1t + x 4 t 2 1 D 2m+1 xt 32 The characteristic polyomials satisfy the followig recursio relatio. 0 D +4 x 2x 2 1D +2 x x 4 D x 33 Followig are the first several characteristic polyomials, D x, where is the degree of the polyomial. D 0 x +1 D 1 x +1 x D 2 x 1 x + x 2 D 3 x 1 + x + 2x 2 x 3 D 4 x +1 + x 3x 2 2x 3 + x 4 D 5 x +1 x 4x 2 + 3x 3 + 3x 4 x 5 D 6 x 1 x + 5x 2 + 4x 3 6x 4 3x 5 + x 6 D 7 x 1 + x + 6x 2 5x 3 10x 4 + 6x 5 + 4x 6 x 7 D 8 x +1 + x 7x 2 6x x x 5 10x 6 4x 7 + x 8 34 The characteristic polyomials ca be expressed as a power series with coefficiets D,j, where is the degree of the polyomial ad j is the degree of the term. D x D,j x j 35 The followig is a Table of the coefficiets of the characteristic polyomials, D,j. j0 7

8 j Table 1: Fiboacci Characteristic Polyomial Coefficiets, D,j Rows represet the coefficiets of the polyomials of degree 8. Right leaig colums represet the coefficiets of the terms of degree j, where 0 j. This Table is remiiscet of Pascal s triagular table of the biomial coefficiets. We shall call it Fiboacci s triagle ad the coefficiets, Fiboacci coefficiets. While the biomial coefficiets are all positive, the Fiboacci coefficiets show a iterestig patter of alteratig positive ad egative sigs. The magitudes of the Fiboacci coefficiets of fixed j vary with icreasig just as the biomial coefficiets do. But while Pascal s triagle is symmetric about the midlie j /2, the Fiboacci triagle is defiitely ot symmetric. The Fiboacci coefficiets are geerated by the followig formula. j + [j/2] D,j 1 j+[ j/2] j Here, the square brackets [ ] idicate the floor or roud-dow fuctio, which yields the largest iteger smaller tha the argumet that the brackets cotai. The characteristic polyomial may ow be writte i terms of the Fiboacci coefficiets. D x 36 j + [j/2] 1 j+[ j/2] x j 37 j j0 This form of the characteristic polyomial is much simpler ad easier to use ad uderstad tha the implicit form of the polyomial derived by Juge ad Hoggatt [2]. It is idetical to explicit form of the polyomials derived by Raey [3] i his Theorem 9. 8

9 Let us fid the recursio relatios obeyed by the Fiboacci characteristic polyomial coefficiets. Substitute the defiitio of the polyomial as a power series, equatio 35, ito the recursio relatio for the polyomials, equatio 33, ad equate terms of the same degree i x. Thus, we fid the followig set of relatios amog the polyomial coefficiets. D +2,0 D,0 D +2,1 D,1 D +2,2 2D,0 D,2 D +2,3 2D,1 D,3 D +4,j+4 2D +2,j+2 D +2,j+4 D,j 38 You may cofirm that the polyomial coefficiets, derived from the formula for them, equatio 36, ad displayed i Table 1, satisfy all these relatios. Now that we have foud the Fiboacci characteristic polyomial coefficiets, let us make some use of them. Earlier, we displayed the recursio relatio, equatio, that defies Fiboacci vector sequeces. From a give vector, it says how to calculate, compoet by compoet, the ext vector i the sequece. Let us ow cosider a related problem. How ca you calculate a particular compoet of the ext vector i the sequece, if you kow, ot the compoets of the oe precedig vector, but the same sigle compoet of the precedig vectors? To fid the solutio to this problem, let us briefly retur to the origial Fiboacci sequece. This sequece is defied, as you well kow, by a recursive relatio: ay umber i the sequece is the sum of the two precedig umbers. F k + 2 F k F k 39 Now, traslate this familiar equatio ito the symbols of Fiboacci vectors ad rearrage a bit. F 2 k, i F 2 k + 1, i + F 2 k + 2, i 0 40 The sigs of the three terms are just the three coefficiets D 2,j of the characteristic polyomial of degree 2. 2 D 2,0 F 2 k, i + D 2,1 F 2 k + 1, i + D 2,2 F 2 k + 2, i D 2,j F k + j, i 0 41 Now, geeralize. Fiboacci vector compoets are recursively related by the followig geeralizatio of the origial Fiboacci recursive relatio. D,j F k + j, i 0 42 j0 We postpoe proof that this relatio amog Fiboacci vector compoets follows from the recursive relatio betwee cosecutive Fiboacci vectors, equatio, which defies Fiboacci vector sequeces. j0 9

10 Now, let s put this geeral priciple ito a form useful for calculatio. Isolate the term of highest degree, F k +, i, the coefficiet of which is D, 1, ad we have the aswer to our problem. 1 F k +, i 1 +1 D,j F k + j, i 0 43 j i+1 j1 j0 The ith compoet of the k +th vector i the sequece, F k +, i, equals the sum from j 0 to j 1 of the products of the ith compoet of the k + jth vector ad the polyomial coefficiet D,j. You ca compute ay compoet of a Fiboacci vector, if you kow the same compoet of the precedig vectors: you multiply each such compoet by the appropriate polyomial coefficiet ad add these products to obtai the result. The golde sum: For a give dimesio ad idex i, 1 i, the sum of the greatest i golde umbers, from r i + 1 to r, is the product of the ith golde umber r i ad the greatest oe golde umber r. i r j r i + j r r i 44 Proof of this rule follows simply from equatio 18 of our earlier paper [1], the golde system of equatios, which may be writte as follows. r j r r j + 1 r j 45 Sum both sides from j 1 to j i 1. i 1 r j j1 1 j i+1 Because r 1 1, the golde sum follows. i 1 r j r r j + 1 r j r r i r 1 46 j1 6. CONCLUSION 10

11 REFERENCES Refereces [1] Stuart D. Aderso ad Dai Novak, Fiboacci Vector Sequeces ad Regular Polygos, Fiboacci Quarterly,??:?,???-??? 20??. [2] Bjare Juge ad V. E. Hoggatt, Jr., Polyomials Arisig from Reflectios across Multiple Plates, Fiboacci Quarterly, 11:3, [3] George N. Raey, Geeralizatio of the Fiboacci Sequece to Dimesios, Ca. J. Math., 18, AMS Classificatio Number: 11B39 11

CALCULATING FIBONACCI VECTORS

CALCULATING FIBONACCI VECTORS THE GENERALIZED BINET FORMULA FOR CALCULATING FIBONACCI VECTORS Stuart D Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithacaedu ad Dai Novak Departmet

More information

Math 155 (Lecture 3)

Math 155 (Lecture 3) Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis Recursive Algorithms Recurreces Computer Sciece & Egieerig 35: Discrete Mathematics Christopher M Bourke cbourke@cseuledu A recursive algorithm is oe i which objects are defied i terms of other objects

More information

Bertrand s Postulate

Bertrand s Postulate Bertrad s Postulate Lola Thompso Ross Program July 3, 2009 Lola Thompso (Ross Program Bertrad s Postulate July 3, 2009 1 / 33 Bertrad s Postulate I ve said it oce ad I ll say it agai: There s always a

More information

A Combinatoric Proof and Generalization of Ferguson s Formula for k-generalized Fibonacci Numbers

A Combinatoric Proof and Generalization of Ferguson s Formula for k-generalized Fibonacci Numbers Jue 5 00 A Combiatoric Proof ad Geeralizatio of Ferguso s Formula for k-geeralized Fiboacci Numbers David Kessler 1 ad Jeremy Schiff 1 Departmet of Physics Departmet of Mathematics Bar-Ila Uiversity, Ramat

More information

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018 CSE 353 Discrete Computatioal Structures Sprig 08 Sequeces, Mathematical Iductio, ad Recursio (Chapter 5, Epp) Note: some course slides adopted from publisher-provided material Overview May mathematical

More information

Chimica Inorganica 3

Chimica Inorganica 3 himica Iorgaica Irreducible Represetatios ad haracter Tables Rather tha usig geometrical operatios, it is ofte much more coveiet to employ a ew set of group elemets which are matrices ad to make the rule

More information

A GENERALIZATION OF THE SYMMETRY BETWEEN COMPLETE AND ELEMENTARY SYMMETRIC FUNCTIONS. Mircea Merca

A GENERALIZATION OF THE SYMMETRY BETWEEN COMPLETE AND ELEMENTARY SYMMETRIC FUNCTIONS. Mircea Merca Idia J Pure Appl Math 45): 75-89 February 204 c Idia Natioal Sciece Academy A GENERALIZATION OF THE SYMMETRY BETWEEN COMPLETE AND ELEMENTARY SYMMETRIC FUNCTIONS Mircea Merca Departmet of Mathematics Uiversity

More information

Orthogonal transformations

Orthogonal transformations Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear

More information

The r-generalized Fibonacci Numbers and Polynomial Coefficients

The r-generalized Fibonacci Numbers and Polynomial Coefficients It. J. Cotemp. Math. Scieces, Vol. 3, 2008, o. 24, 1157-1163 The r-geeralized Fiboacci Numbers ad Polyomial Coefficiets Matthias Schork Camillo-Sitte-Weg 25 60488 Frakfurt, Germay mschork@member.ams.org,

More information

Recurrence Relations

Recurrence Relations Recurrece Relatios Aalysis of recursive algorithms, such as: it factorial (it ) { if (==0) retur ; else retur ( * factorial(-)); } Let t be the umber of multiplicatios eeded to calculate factorial(). The

More information

MAT 271 Project: Partial Fractions for certain rational functions

MAT 271 Project: Partial Fractions for certain rational functions MAT 7 Project: Partial Fractios for certai ratioal fuctios Prerequisite kowledge: partial fractios from MAT 7, a very good commad of factorig ad complex umbers from Precalculus. To complete this project,

More information

Generating Functions. 1 Operations on generating functions

Generating Functions. 1 Operations on generating functions Geeratig Fuctios The geeratig fuctio for a sequece a 0, a,..., a,... is defied to be the power series fx a x. 0 We say that a 0, a,... is the sequece geerated by fx ad a is the coefficiet of x. Example

More information

R is a scalar defined as follows:

R is a scalar defined as follows: Math 8. Notes o Dot Product, Cross Product, Plaes, Area, ad Volumes This lecture focuses primarily o the dot product ad its may applicatios, especially i the measuremet of agles ad scalar projectio ad

More information

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3 MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special

More information

In number theory we will generally be working with integers, though occasionally fractions and irrationals will come into play.

In number theory we will generally be working with integers, though occasionally fractions and irrationals will come into play. Number Theory Math 5840 otes. Sectio 1: Axioms. I umber theory we will geerally be workig with itegers, though occasioally fractios ad irratioals will come ito play. Notatio: Z deotes the set of all itegers

More information

A Simplified Binet Formula for k-generalized Fibonacci Numbers

A Simplified Binet Formula for k-generalized Fibonacci Numbers A Simplified Biet Formula for k-geeralized Fiboacci Numbers Gregory P. B. Dresde Departmet of Mathematics Washigto ad Lee Uiversity Lexigto, VA 440 dresdeg@wlu.edu Zhaohui Du Shaghai, Chia zhao.hui.du@gmail.com

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains.

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains. The mai ideas are: Idetities REVISION SHEET FP (MEI) ALGEBRA Before the exam you should kow: If a expressio is a idetity the it is true for all values of the variable it cotais The relatioships betwee

More information

PROPERTIES OF AN EULER SQUARE

PROPERTIES OF AN EULER SQUARE PROPERTIES OF N EULER SQURE bout 0 the mathematicia Leoard Euler discussed the properties a x array of letters or itegers ow kow as a Euler or Graeco-Lati Square Such squares have the property that every

More information

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Inverse Matrix. A meaning that matrix B is an inverse of matrix A. Iverse Matrix Two square matrices A ad B of dimesios are called iverses to oe aother if the followig holds, AB BA I (11) The otio is dual but we ofte write 1 B A meaig that matrix B is a iverse of matrix

More information

The Random Walk For Dummies

The Random Walk For Dummies The Radom Walk For Dummies Richard A Mote Abstract We look at the priciples goverig the oe-dimesioal discrete radom walk First we review five basic cocepts of probability theory The we cosider the Beroulli

More information

NICK DUFRESNE. 1 1 p(x). To determine some formulas for the generating function of the Schröder numbers, r(x) = a(x) =

NICK DUFRESNE. 1 1 p(x). To determine some formulas for the generating function of the Schröder numbers, r(x) = a(x) = AN INTRODUCTION TO SCHRÖDER AND UNKNOWN NUMBERS NICK DUFRESNE Abstract. I this article we will itroduce two types of lattice paths, Schröder paths ad Ukow paths. We will examie differet properties of each,

More information

6.003 Homework #3 Solutions

6.003 Homework #3 Solutions 6.00 Homework # Solutios Problems. Complex umbers a. Evaluate the real ad imagiary parts of j j. π/ Real part = Imagiary part = 0 e Euler s formula says that j = e jπ/, so jπ/ j π/ j j = e = e. Thus the

More information

Chapter Vectors

Chapter Vectors Chapter 4. Vectors fter readig this chapter you should be able to:. defie a vector. add ad subtract vectors. fid liear combiatios of vectors ad their relatioship to a set of equatios 4. explai what it

More information

Week 5-6: The Binomial Coefficients

Week 5-6: The Binomial Coefficients Wee 5-6: The Biomial Coefficiets March 6, 2018 1 Pascal Formula Theorem 11 (Pascal s Formula For itegers ad such that 1, ( ( ( 1 1 + 1 The umbers ( 2 ( 1 2 ( 2 are triagle umbers, that is, The petago umbers

More information

CHAPTER I: Vector Spaces

CHAPTER I: Vector Spaces CHAPTER I: Vector Spaces Sectio 1: Itroductio ad Examples This first chapter is largely a review of topics you probably saw i your liear algebra course. So why cover it? (1) Not everyoe remembers everythig

More information

CSE 1400 Applied Discrete Mathematics Number Theory and Proofs

CSE 1400 Applied Discrete Mathematics Number Theory and Proofs CSE 1400 Applied Discrete Mathematics Number Theory ad Proofs Departmet of Computer Scieces College of Egieerig Florida Tech Sprig 01 Problems for Number Theory Backgroud Number theory is the brach of

More information

1 Last time: similar and diagonalizable matrices

1 Last time: similar and diagonalizable matrices Last time: similar ad diagoalizable matrices Let be a positive iteger Suppose A is a matrix, v R, ad λ R Recall that v a eigevector for A with eigevalue λ if v ad Av λv, or equivaletly if v is a ozero

More information

Math 475, Problem Set #12: Answers

Math 475, Problem Set #12: Answers Math 475, Problem Set #12: Aswers A. Chapter 8, problem 12, parts (b) ad (d). (b) S # (, 2) = 2 2, sice, from amog the 2 ways of puttig elemets ito 2 distiguishable boxes, exactly 2 of them result i oe

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 50-004 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains.

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains. the Further Mathematics etwork wwwfmetworkorguk V 07 The mai ideas are: Idetities REVISION SHEET FP (MEI) ALGEBRA Before the exam you should kow: If a expressio is a idetity the it is true for all values

More information

MT5821 Advanced Combinatorics

MT5821 Advanced Combinatorics MT5821 Advaced Combiatorics 9 Set partitios ad permutatios It could be said that the mai objects of iterest i combiatorics are subsets, partitios ad permutatios of a fiite set. We have spet some time coutig

More information

arxiv: v1 [math.fa] 3 Apr 2016

arxiv: v1 [math.fa] 3 Apr 2016 Aticommutator Norm Formula for Proectio Operators arxiv:164.699v1 math.fa] 3 Apr 16 Sam Walters Uiversity of Norther British Columbia ABSTRACT. We prove that for ay two proectio operators f, g o Hilbert

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Sequeces ad 6 Sequeces Ad SEQUENCES AND SERIES Successio of umbers of which oe umber is desigated as the first, other as the secod, aother as the third ad so o gives rise to what is called a sequece. Sequeces

More information

Determinants of order 2 and 3 were defined in Chapter 2 by the formulae (5.1)

Determinants of order 2 and 3 were defined in Chapter 2 by the formulae (5.1) 5. Determiats 5.. Itroductio 5.2. Motivatio for the Choice of Axioms for a Determiat Fuctios 5.3. A Set of Axioms for a Determiat Fuctio 5.4. The Determiat of a Diagoal Matrix 5.5. The Determiat of a Upper

More information

Roger Apéry's proof that zeta(3) is irrational

Roger Apéry's proof that zeta(3) is irrational Cliff Bott cliffbott@hotmail.com 11 October 2011 Roger Apéry's proof that zeta(3) is irratioal Roger Apéry developed a method for searchig for cotiued fractio represetatios of umbers that have a form such

More information

Math 61CM - Solutions to homework 3

Math 61CM - Solutions to homework 3 Math 6CM - Solutios to homework 3 Cédric De Groote October 2 th, 208 Problem : Let F be a field, m 0 a fixed oegative iteger ad let V = {a 0 + a x + + a m x m a 0,, a m F} be the vector space cosistig

More information

DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS

DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS VERNER E. HOGGATT, JR. Sa Jose State Uiversity, Sa Jose, Califoria 95192 ad CALVIN T. LONG Washigto State Uiversity, Pullma, Washigto 99163

More information

Intermediate Math Circles November 4, 2009 Counting II

Intermediate Math Circles November 4, 2009 Counting II Uiversity of Waterloo Faculty of Mathematics Cetre for Educatio i Mathematics ad Computig Itermediate Math Circles November 4, 009 Coutig II Last time, after lookig at the product rule ad sum rule, we

More information

SOME TRIBONACCI IDENTITIES

SOME TRIBONACCI IDENTITIES Mathematics Today Vol.7(Dec-011) 1-9 ISSN 0976-38 Abstract: SOME TRIBONACCI IDENTITIES Shah Devbhadra V. Sir P.T.Sarvajaik College of Sciece, Athwalies, Surat 395001. e-mail : drdvshah@yahoo.com The sequece

More information

Sigma notation. 2.1 Introduction

Sigma notation. 2.1 Introduction Sigma otatio. Itroductio We use sigma otatio to idicate the summatio process whe we have several (or ifiitely may) terms to add up. You may have see sigma otatio i earlier courses. It is used to idicate

More information

Complex Numbers Solutions

Complex Numbers Solutions Complex Numbers Solutios Joseph Zoller February 7, 06 Solutios. (009 AIME I Problem ) There is a complex umber with imagiary part 64 ad a positive iteger such that Fid. [Solutio: 697] 4i + + 4i. 4i 4i

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e.

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e. Theorem: Let A be a square matrix The A has a iverse matrix if ad oly if its reduced row echelo form is the idetity I this case the algorithm illustrated o the previous page will always yield the iverse

More information

1 Generating functions for balls in boxes

1 Generating functions for balls in boxes Math 566 Fall 05 Some otes o geeratig fuctios Give a sequece a 0, a, a,..., a,..., a geeratig fuctio some way of represetig the sequece as a fuctio. There are may ways to do this, with the most commo ways

More information

2.4 - Sequences and Series

2.4 - Sequences and Series 2.4 - Sequeces ad Series Sequeces A sequece is a ordered list of elemets. Defiitio 1 A sequece is a fuctio from a subset of the set of itegers (usually either the set 80, 1, 2, 3,... < or the set 81, 2,

More information

Matrices and vectors

Matrices and vectors Oe Matrices ad vectors This book takes for grated that readers have some previous kowledge of the calculus of real fuctios of oe real variable It would be helpful to also have some kowledge of liear algebra

More information

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx)

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx) Cosider the differetial equatio y '' k y 0 has particular solutios y1 si( kx) ad y cos( kx) I geeral, ay liear combiatio of y1 ad y, cy 1 1 cy where c1, c is also a solutio to the equatio above The reaso

More information

Section 5.1 The Basics of Counting

Section 5.1 The Basics of Counting 1 Sectio 5.1 The Basics of Coutig Combiatorics, the study of arragemets of objects, is a importat part of discrete mathematics. I this chapter, we will lear basic techiques of coutig which has a lot of

More information

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a Math E-2b Lecture #8 Notes This week is all about determiats. We ll discuss how to defie them, how to calculate them, lear the allimportat property kow as multiliearity, ad show that a square matrix A

More information

P. Z. Chinn Department of Mathematics, Humboldt State University, Arcata, CA

P. Z. Chinn Department of Mathematics, Humboldt State University, Arcata, CA RISES, LEVELS, DROPS AND + SIGNS IN COMPOSITIONS: EXTENSIONS OF A PAPER BY ALLADI AND HOGGATT S. Heubach Departmet of Mathematics, Califoria State Uiversity Los Ageles 55 State Uiversity Drive, Los Ageles,

More information

MATH 304: MIDTERM EXAM SOLUTIONS

MATH 304: MIDTERM EXAM SOLUTIONS MATH 304: MIDTERM EXAM SOLUTIONS [The problems are each worth five poits, except for problem 8, which is worth 8 poits. Thus there are 43 possible poits.] 1. Use the Euclidea algorithm to fid the greatest

More information

M A T H F A L L CORRECTION. Algebra I 1 4 / 1 0 / U N I V E R S I T Y O F T O R O N T O

M A T H F A L L CORRECTION. Algebra I 1 4 / 1 0 / U N I V E R S I T Y O F T O R O N T O M A T H 2 4 0 F A L L 2 0 1 4 HOMEWORK ASSIGNMENT #4 CORRECTION Algebra I 1 4 / 1 0 / 2 0 1 4 U N I V E R S I T Y O F T O R O N T O P r o f e s s o r : D r o r B a r - N a t a Correctio Homework Assigmet

More information

ANOTHER GENERALIZED FIBONACCI SEQUENCE 1. INTRODUCTION

ANOTHER GENERALIZED FIBONACCI SEQUENCE 1. INTRODUCTION ANOTHER GENERALIZED FIBONACCI SEQUENCE MARCELLUS E. WADDILL A N D LOUIS SACKS Wake Forest College, Wisto Salem, N. C., ad Uiversity of ittsburgh, ittsburgh, a. 1. INTRODUCTION Recet issues of umerous periodicals

More information

MAT1026 Calculus II Basic Convergence Tests for Series

MAT1026 Calculus II Basic Convergence Tests for Series MAT026 Calculus II Basic Covergece Tests for Series Egi MERMUT 202.03.08 Dokuz Eylül Uiversity Faculty of Sciece Departmet of Mathematics İzmir/TURKEY Cotets Mootoe Covergece Theorem 2 2 Series of Real

More information

CALCULUS BASIC SUMMER REVIEW

CALCULUS BASIC SUMMER REVIEW CALCULUS BASIC SUMMER REVIEW NAME rise y y y Slope of a o vertical lie: m ru Poit Slope Equatio: y y m( ) The slope is m ad a poit o your lie is, ). ( y Slope-Itercept Equatio: y m b slope= m y-itercept=

More information

Chapter 7 COMBINATIONS AND PERMUTATIONS. where we have the specific formula for the binomial coefficients:

Chapter 7 COMBINATIONS AND PERMUTATIONS. where we have the specific formula for the binomial coefficients: Chapter 7 COMBINATIONS AND PERMUTATIONS We have see i the previous chapter that (a + b) ca be writte as 0 a % a & b%þ% a & b %þ% b where we have the specific formula for the biomial coefficiets: '!!(&)!

More information

REVIEW FOR CHAPTER 1

REVIEW FOR CHAPTER 1 REVIEW FOR CHAPTER 1 A short summary: I this chapter you helped develop some basic coutig priciples. I particular, the uses of ordered pairs (The Product Priciple), fuctios, ad set partitios (The Sum Priciple)

More information

2.4 Sequences, Sequences of Sets

2.4 Sequences, Sequences of Sets 72 CHAPTER 2. IMPORTANT PROPERTIES OF R 2.4 Sequeces, Sequeces of Sets 2.4.1 Sequeces Defiitio 2.4.1 (sequece Let S R. 1. A sequece i S is a fuctio f : K S where K = { N : 0 for some 0 N}. 2. For each

More information

CHAPTER 10 INFINITE SEQUENCES AND SERIES

CHAPTER 10 INFINITE SEQUENCES AND SERIES CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece

More information

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and

Filter banks. Separately, the lowpass and highpass filters are not invertible. removes the highest frequency 1/ 2and Filter bas Separately, the lowpass ad highpass filters are ot ivertible T removes the highest frequecy / ad removes the lowest frequecy Together these filters separate the sigal ito low-frequecy ad high-frequecy

More information

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a Math S-b Lecture # Notes This wee is all about determiats We ll discuss how to defie them, how to calculate them, lear the allimportat property ow as multiliearity, ad show that a square matrix A is ivertible

More information

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities Polyomials with Ratioal Roots that Differ by a No-zero Costat Philip Gibbs The problem of fidig two polyomials P(x) ad Q(x) of a give degree i a sigle variable x that have all ratioal roots ad differ by

More information

Assignment 2 Solutions SOLUTION. ϕ 1 Â = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ.

Assignment 2 Solutions SOLUTION. ϕ 1  = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ. PHYSICS 34 QUANTUM PHYSICS II (25) Assigmet 2 Solutios 1. With respect to a pair of orthoormal vectors ϕ 1 ad ϕ 2 that spa the Hilbert space H of a certai system, the operator  is defied by its actio

More information

18th Bay Area Mathematical Olympiad. Problems and Solutions. February 23, 2016

18th Bay Area Mathematical Olympiad. Problems and Solutions. February 23, 2016 18th Bay Area Mathematical Olympiad February 3, 016 Problems ad Solutios BAMO-8 ad BAMO-1 are each 5-questio essay-proof exams, for middle- ad high-school studets, respectively. The problems i each exam

More information

1. n! = n. tion. For example, (n+1)! working with factorials. = (n+1) n (n 1) 2 1

1. n! = n. tion. For example, (n+1)! working with factorials. = (n+1) n (n 1) 2 1 Biomial Coefficiets ad Permutatios Mii-lecture The followig pages discuss a few special iteger coutig fuctios You may have see some of these before i a basic probability class or elsewhere, but perhaps

More information

is also known as the general term of the sequence

is also known as the general term of the sequence Lesso : Sequeces ad Series Outlie Objectives: I ca determie whether a sequece has a patter. I ca determie whether a sequece ca be geeralized to fid a formula for the geeral term i the sequece. I ca determie

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES 9 SEQUENCES AND SERIES INTRODUCTION Sequeces have may importat applicatios i several spheres of huma activities Whe a collectio of objects is arraged i a defiite order such that it has a idetified first

More information

~W I F

~W I F A FIBONACCI PROPERTY OF WYTHOFF PAIRS ROBERT SILBER North Carolia State Uiversity, Raleigh, North Carolia 27607 I this paper we poit out aother of those fasciatig "coicideces" which are so characteristically

More information

USA Mathematical Talent Search Round 3 Solutions Year 27 Academic Year

USA Mathematical Talent Search Round 3 Solutions Year 27 Academic Year /3/27. Fill i each space of the grid with either a or a so that all sixtee strigs of four cosecutive umbers across ad dow are distict. You do ot eed to prove that your aswer is the oly oe possible; you

More information

Math 113 Exam 3 Practice

Math 113 Exam 3 Practice Math Exam Practice Exam will cover.-.9. This sheet has three sectios. The first sectio will remid you about techiques ad formulas that you should kow. The secod gives a umber of practice questios for you

More information

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled

The picture in figure 1.1 helps us to see that the area represents the distance traveled. Figure 1: Area represents distance travelled 1 Lecture : Area Area ad distace traveled Approximatig area by rectagles Summatio The area uder a parabola 1.1 Area ad distace Suppose we have the followig iformatio about the velocity of a particle, how

More information

The Discrete Fourier Transform

The Discrete Fourier Transform The Discrete Fourier Trasform Complex Fourier Series Represetatio Recall that a Fourier series has the form a 0 + a k cos(kt) + k=1 b k si(kt) This represetatio seems a bit awkward, sice it ivolves two

More information

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece 1, 1, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet

More information

subcaptionfont+=small,labelformat=parens,labelsep=space,skip=6pt,list=0,hypcap=0 subcaption ALGEBRAIC COMBINATORICS LECTURE 8 TUESDAY, 2/16/2016

subcaptionfont+=small,labelformat=parens,labelsep=space,skip=6pt,list=0,hypcap=0 subcaption ALGEBRAIC COMBINATORICS LECTURE 8 TUESDAY, 2/16/2016 subcaptiofot+=small,labelformat=pares,labelsep=space,skip=6pt,list=0,hypcap=0 subcaptio ALGEBRAIC COMBINATORICS LECTURE 8 TUESDAY, /6/06. Self-cojugate Partitios Recall that, give a partitio λ, we may

More information

P1 Chapter 8 :: Binomial Expansion

P1 Chapter 8 :: Binomial Expansion P Chapter 8 :: Biomial Expasio jfrost@tiffi.kigsto.sch.uk www.drfrostmaths.com @DrFrostMaths Last modified: 6 th August 7 Use of DrFrostMaths for practice Register for free at: www.drfrostmaths.com/homework

More information

Hoggatt and King [lo] defined a complete sequence of natural numbers

Hoggatt and King [lo] defined a complete sequence of natural numbers REPRESENTATIONS OF N AS A SUM OF DISTINCT ELEMENTS FROM SPECIAL SEQUENCES DAVID A. KLARNER, Uiversity of Alberta, Edmoto, Caada 1. INTRODUCTION Let a, I deote a sequece of atural umbers which satisfies

More information

CERTAIN GENERAL BINOMIAL-FIBONACCI SUMS

CERTAIN GENERAL BINOMIAL-FIBONACCI SUMS CERTAIN GENERAL BINOMIAL-FIBONACCI SUMS J. W. LAYMAN Virgiia Polytechic Istitute State Uiversity, Blacksburg, Virgiia Numerous writers appear to have bee fasciated by the may iterestig summatio idetitites

More information

CHAPTER 5. Theory and Solution Using Matrix Techniques

CHAPTER 5. Theory and Solution Using Matrix Techniques A SERIES OF CLASS NOTES FOR 2005-2006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 3 A COLLECTION OF HANDOUTS ON SYSTEMS OF ORDINARY DIFFERENTIAL

More information

September 2012 C1 Note. C1 Notes (Edexcel) Copyright - For AS, A2 notes and IGCSE / GCSE worksheets 1

September 2012 C1 Note. C1 Notes (Edexcel) Copyright   - For AS, A2 notes and IGCSE / GCSE worksheets 1 September 0 s (Edecel) Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright

More information

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function.

It is always the case that unions, intersections, complements, and set differences are preserved by the inverse image of a function. MATH 532 Measurable Fuctios Dr. Neal, WKU Throughout, let ( X, F, µ) be a measure space ad let (!, F, P ) deote the special case of a probability space. We shall ow begi to study real-valued fuctios defied

More information

SEQUENCE AND SERIES NCERT

SEQUENCE AND SERIES NCERT 9. Overview By a sequece, we mea a arragemet of umbers i a defiite order accordig to some rule. We deote the terms of a sequece by a, a,..., etc., the subscript deotes the positio of the term. I view of

More information

UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST. First Round For all Colorado Students Grades 7-12 November 3, 2007

UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST. First Round For all Colorado Students Grades 7-12 November 3, 2007 UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST First Roud For all Colorado Studets Grades 7- November, 7 The positive itegers are,,, 4, 5, 6, 7, 8, 9,,,,. The Pythagorea Theorem says that a + b =

More information

11. FINITE FIELDS. Example 1: The following tables define addition and multiplication for a field of order 4.

11. FINITE FIELDS. Example 1: The following tables define addition and multiplication for a field of order 4. 11. FINITE FIELDS 11.1. A Field With 4 Elemets Probably the oly fiite fields which you ll kow about at this stage are the fields of itegers modulo a prime p, deoted by Z p. But there are others. Now although

More information

Math 312 Lecture Notes One Dimensional Maps

Math 312 Lecture Notes One Dimensional Maps Math 312 Lecture Notes Oe Dimesioal Maps Warre Weckesser Departmet of Mathematics Colgate Uiversity 21-23 February 25 A Example We begi with the simplest model of populatio growth. Suppose, for example,

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

EVALUATION OF SUMS INVOLVING PRODUCTS OF GAUSSIAN q-binomial COEFFICIENTS WITH APPLICATIONS

EVALUATION OF SUMS INVOLVING PRODUCTS OF GAUSSIAN q-binomial COEFFICIENTS WITH APPLICATIONS EALATION OF SMS INOLING PRODCTS OF GASSIAN -BINOMIAL COEFFICIENTS WITH APPLICATIONS EMRAH KILIÇ* AND HELMT PRODINGER** Abstract Sums of products of two Gaussia -biomial coefficiets are ivestigated oe of

More information

Random Models. Tusheng Zhang. February 14, 2013

Random Models. Tusheng Zhang. February 14, 2013 Radom Models Tusheg Zhag February 14, 013 1 Radom Walks Let me describe the model. Radom walks are used to describe the motio of a movig particle (object). Suppose that a particle (object) moves alog the

More information

On Generalized Fibonacci Numbers

On Generalized Fibonacci Numbers Applied Mathematical Scieces, Vol. 9, 215, o. 73, 3611-3622 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/1.12988/ams.215.5299 O Geeralized Fiboacci Numbers Jerico B. Bacai ad Julius Fergy T. Rabago Departmet

More information

Unit 6: Sequences and Series

Unit 6: Sequences and Series AMHS Hoors Algebra 2 - Uit 6 Uit 6: Sequeces ad Series 26 Sequeces Defiitio: A sequece is a ordered list of umbers ad is formally defied as a fuctio whose domai is the set of positive itegers. It is commo

More information

SNAP Centre Workshop. Basic Algebraic Manipulation

SNAP Centre Workshop. Basic Algebraic Manipulation SNAP Cetre Workshop Basic Algebraic Maipulatio 8 Simplifyig Algebraic Expressios Whe a expressio is writte i the most compact maer possible, it is cosidered to be simplified. Not Simplified: x(x + 4x)

More information

RADICAL EXPRESSION. If a and x are real numbers and n is a positive integer, then x is an. n th root theorems: Example 1 Simplify

RADICAL EXPRESSION. If a and x are real numbers and n is a positive integer, then x is an. n th root theorems: Example 1 Simplify Example 1 Simplify 1.2A Radical Operatios a) 4 2 b) 16 1 2 c) 16 d) 2 e) 8 1 f) 8 What is the relatioship betwee a, b, c? What is the relatioship betwee d, e, f? If x = a, the x = = th root theorems: RADICAL

More information

Matrix Algebra 2.2 THE INVERSE OF A MATRIX Pearson Education, Inc.

Matrix Algebra 2.2 THE INVERSE OF A MATRIX Pearson Education, Inc. 2 Matrix Algebra 2.2 THE INVERSE OF A MATRIX MATRIX OPERATIONS A matrix A is said to be ivertible if there is a matrix C such that CA = I ad AC = I where, the idetity matrix. I = I I this case, C is a

More information

Permutations, Combinations, and the Binomial Theorem

Permutations, Combinations, and the Binomial Theorem Permutatios, ombiatios, ad the Biomial Theorem Sectio Permutatios outig methods are used to determie the umber of members of a specific set as well as outcomes of a evet. There are may differet ways to

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

A FIBONACCI MATRIX AND THE PERMANENT FUNCTION

A FIBONACCI MATRIX AND THE PERMANENT FUNCTION A FIBONACCI MATRIX AND THE PERMANENT FUNCTION BRUCE W. KING Burt Hiils-Ballsto Lake High School, Ballsto Lake, New York ad FRANCIS D. PARKER The St. Lawrece Uiversity, Cato, New York The permaet of a -square

More information

Complex Analysis Spring 2001 Homework I Solution

Complex Analysis Spring 2001 Homework I Solution Complex Aalysis Sprig 2001 Homework I Solutio 1. Coway, Chapter 1, sectio 3, problem 3. Describe the set of poits satisfyig the equatio z a z + a = 2c, where c > 0 ad a R. To begi, we see from the triagle

More information