Fast Fourier Transform 1) Legendre s Interpolation 2) Vandermonde Matrix 3) Roots of Unity 4) Polynomial Evaluation

Size: px
Start display at page:

Download "Fast Fourier Transform 1) Legendre s Interpolation 2) Vandermonde Matrix 3) Roots of Unity 4) Polynomial Evaluation"

Transcription

1 Algorithm Desig d Alsis Victor Admchi CS 5-45 Sprig 4 Lecture 3 J 7, 4 Cregie Mello Uiversit Outlie Fst Fourier Trsform ) Legedre s Iterpoltio ) Vdermode Mtri 3) Roots of Uit 4) Polomil Evlutio Guss ( ) Lgrge (736 83) Fourier (768 83) High Level Ide The orst-cse compleit To compute the polomil (order ) product A()B(), ) evlute A() d B() t some (+) poits, ) multipl A( )B( ), 3) the fid the polomil hich psses through these poits. To compute the polomil product A()B(), ) evlute A() d B() t some poits, - ht s the compleit of A( )-? - ht s the compleit of A( ) t poits? ) multipl A( )B( ), 3) the fid the polomil hich psses through these poits. - ho c e do it? Wht is it compleit? Iterpoltio Give set of poits Iterpoltio Give pirs (, ), (, ),, (, ) (, ) ( 3, 3 ) ( 5, 5 ) Theorem: There is ectl oe polomil P() of degree t most such tht P( ) = for ll =,,. ( 4,b 4 ) Fid (lo-degree) polomil hich fits the dt

2 Theorem Proof There re to thigs to prove.. There is t lest oe polomil of degree pssig through ll + dt poits.. There is t most oe polomil of degree pssig through ll + dt poits. Let s prove # first. Proof #: There is t most oe polomil Suppose P() d Q() both do the tric. Let R() = P() Q(). Sice deg(p), deg(q) e must hve deg(r). But R( ) = b b = for ll =,,. Thus R() hs more roots (+) th its degree. Thus, R() must be the polomil, i.e., P()=Q(). Proof # Lgrge Iterpoltio The method for costructig the polomil is clled Lgrge s Iterpoltio. Discovered i 795 b J.-L. Lgrge. - b b b b - b Wt P() ith degree such tht P( ) = b. Specil Cse - Oce e solve this specil cse, the geerl cse is ver es. Specil Cse - Let Q() = ( )( )( ) Degree is. Q( ) = Q ( ) = = Q ( ) =. Q( ) =??

3 Numertor is deg. polomil Lgrge Iterpoltio - Deomitor is ozero field elemet Q() ( )( ) S () Q( ) ( )( ) Cll this the selector polomil for. Aother specil cse - ( - )( )( ) S () ( )( )( ) Lgrge Iterpoltio Gret! But ht bout this dt? b b b - - b - b ( )( - ) S () ( )( ) - P() = b S () + + b S () This formul is clled Lrge s Iterpoltio Lgrge Iterpoltio Give pirs (, ), (, ),, (, ) There is uique polomil to fit these poits: () Emple Give to polomils A() = + + B() = Compute their vlues t = -, -,,, {A(-), A(-), A(), A(), A()} = {3,,, 3, 7} {B(-), B(-), B(), B(), B()} = {9,,, 6, 7} Poitise multiplictio: {C(-), C(-), C(), C(), C()} = {7,,, 8, 9} 3

4 4 Emple Poits to fit (-,7), (-,), (, ), (, 8), (, 9) This ields () () Wht is the rutime compleit of Lgrge s iterpoltio? O( 3 ), if e epd () Mtri Form Cosider cse of to poits This could be ritte i mtri form tht defies d. The Vdermode Mtri The Lgrge formul defies polomil here coefficiets c be foud b solvig this or i short V. = A() Thus, = V -. The Vdermode Mtri V I order to iverse the mtri V, e hve to prove tht it s osigulr. Determit of the Vdermode Mtri - ) ( det Sice the + poits re distict, the determit c't be zero. The proof (b iductio o ) is left s eercise to studet

5 Compleit of Iterpoltio It follos tht the compleit of iterpoltio depeds o ho fst c e iverse the Vdermode mtri. Lgrge s Iterpoltio formul c be represeted vi the Vdermode Mtri. The success depeds o the vlues of, =,, Computig Polomils Give polomil of degree. Wht is the compleit of computig its vlue t sigle poit, A( )? Horer s Rule: A() O() Computig Polomils So e compute the sigle vlue i lier time. Therefore, it tes O( ) to compute polomil of degree t poits. I the et slides e ill develop e method tht hs O( log ) rutime compleit. A() ( ( ( )) Computig Polomils The e ide is to use the divide-d-coquer lgorithm. We split polomil ito to prts: ith eve d odd degree terms. For emple, A() = A ( ) + A ( ) =( )+( ) Worst-time Compleit Let T() be the compleit of computig degree- polomil t + poits. Thus T() T(/) O() This solves to O( log ). Gret! The ol problem is tht the lgorithm requires of hvig hlf positive d hlf egtive poits o ech itertio. 5

6 Ver specil poits A() = A ( ) + A ( ) So, e eed to fid such set of poits tht ) hlf of poits re egtive d the secod hlf is positive Roots of Uit The re defied s solutios to z =. Here is = 8 - i i +i i π/4 i e + ) this propert holds fter squrig i -i i i Comple umbers o uit circle re represeted b z = e i =cos() + i si() Roots of Uit: = 8 Let = i, the roots of z 8 = c be ritte s,,, 3, 4, 5, 6, 7 Sice i = -, d thus 4 = -, the c lso be ritte s,,, 3, -, -, -, - 3 Let us te hlf d squre them (,,, 3 ) = (,, 4, 6 ) = (,, -, - ) Do it gi (, ) = (, 4 ) = (, -) Computig Polomils Give polomil of degree. A() Our ts to compute A(), A(), A( ), here + =. We c rite these computtios i mtri form!!! Computig Polomils A() A() A( ) A() Lgrge s Iterpoltio formul c be represeted vi the Vdermode Mtri. Polomil evlutio is lso computed vi the Vdermode Mtri. This is the Vdermode mtri. We ill prove tht this mtri multiplictio c be doe i O( log ) 6

7 High Level Ide To compute the product A()B() of polomils (of order ) O( log ) ) evlute A() d B() t (+) roots of uit, usig the Vdermode mtri ) multipl A( )B( ), O() 3) the fid the polomil usig Lgrge s iterpoltio vi the Vdermode mtri O( log ) 7

Interpolation. 1. What is interpolation?

Interpolation. 1. What is interpolation? Iterpoltio. Wht is iterpoltio? A uctio is ote give ol t discrete poits such s:.... How does oe id the vlue o t other vlue o? Well cotiuous uctio m e used to represet the + dt vlues with pssig through the

More information

Lesson 4 Linear Algebra

Lesson 4 Linear Algebra Lesso Lier Algebr A fmily of vectors is lierly idepedet if oe of them c be writte s lier combitio of fiitely my other vectors i the collectio. Cosider m lierly idepedet equtios i ukows:, +, +... +, +,

More information

SOLUTION OF SYSTEM OF LINEAR EQUATIONS. Lecture 4: (a) Jacobi's method. method (general). (b) Gauss Seidel method.

SOLUTION OF SYSTEM OF LINEAR EQUATIONS. Lecture 4: (a) Jacobi's method. method (general). (b) Gauss Seidel method. SOLUTION OF SYSTEM OF LINEAR EQUATIONS Lecture 4: () Jcobi's method. method (geerl). (b) Guss Seidel method. Jcobi s Method: Crl Gustv Jcob Jcobi (804-85) gve idirect method for fidig the solutio of system

More information

Chapter System of Equations

Chapter System of Equations hpter 4.5 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee

More information

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k. . Computtio of Fourier Series I this sectio, we compute the Fourier coefficiets, f ( x) cos( x) b si( x) d b, i the Fourier series To do this, we eed the followig result o the orthogolity of the trigoometric

More information

Graphing Review Part 3: Polynomials

Graphing Review Part 3: Polynomials Grphig Review Prt : Polomils Prbols Recll, tht the grph of f ( ) is prbol. It is eve fuctio, hece it is smmetric bout the bout the -is. This mes tht f ( ) f ( ). Its grph is show below. The poit ( 0,0)

More information

Section 7.3, Systems of Linear Algebraic Equations; Linear Independence, Eigenvalues, Eigenvectors (the variable vector of the system) and

Section 7.3, Systems of Linear Algebraic Equations; Linear Independence, Eigenvalues, Eigenvectors (the variable vector of the system) and Sec. 7., Boyce & DiPrim, p. Sectio 7., Systems of Lier Algeric Equtios; Lier Idepedece, Eigevlues, Eigevectors I. Systems of Lier Algeric Equtios.. We c represet the system...... usig mtrices d vectors

More information

Lecture 4 Recursive Algorithm Analysis. Merge Sort Solving Recurrences The Master Theorem

Lecture 4 Recursive Algorithm Analysis. Merge Sort Solving Recurrences The Master Theorem Lecture 4 Recursive Algorithm Alysis Merge Sort Solvig Recurreces The Mster Theorem Merge Sort MergeSortA, left, right) { if left < right) { mid floorleft right) / 2); MergeSortA, left, mid); MergeSortA,

More information

Lecture 4 Recursive Algorithm Analysis. Merge Sort Solving Recurrences The Master Theorem

Lecture 4 Recursive Algorithm Analysis. Merge Sort Solving Recurrences The Master Theorem Lecture 4 Recursive Algorithm Alysis Merge Sort Solvig Recurreces The Mster Theorem Merge Sort MergeSortA, left, right) { if left < right) { mid = floorleft + right) / 2); MergeSortA, left, mid); MergeSortA,

More information

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best Tylor Polyomils Let f () = e d let p() = 1 + + 1 + 1 6 3 Without usig clcultor, evlute f (1) d p(1) Ok, I m still witig With little effort it is possible to evlute p(1) = 1 + 1 + 1 (144) + 6 1 (178) =

More information

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2!

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2! mth power series, prt ii 7 A Very Iterestig Emple Oe of the first power series we emied ws! + +! + + +!! + I Emple 58 we used the rtio test to show tht the itervl of covergece ws (, ) Sice the series coverges

More information

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions Qudrtic Equtios ALGEBRA Remider theorem: If f() is divided b( ), the remider is f(). Fctor theorem: If ( ) is fctor of f(), the f() = 0. Ivolutio d Evlutio ( + b) = + b + b ( b) = + b b ( + b) 3 = 3 +

More information

M3P14 EXAMPLE SHEET 1 SOLUTIONS

M3P14 EXAMPLE SHEET 1 SOLUTIONS M3P14 EXAMPLE SHEET 1 SOLUTIONS 1. Show tht for, b, d itegers, we hve (d, db) = d(, b). Sice (, b) divides both d b, d(, b) divides both d d db, d hece divides (d, db). O the other hd, there exist m d

More information

[ 20 ] 1. Inequality exists only between two real numbers (not complex numbers). 2. If a be any real number then one and only one of there hold.

[ 20 ] 1. Inequality exists only between two real numbers (not complex numbers). 2. If a be any real number then one and only one of there hold. [ 0 ]. Iequlity eists oly betwee two rel umbers (ot comple umbers).. If be y rel umber the oe d oly oe of there hold.. If, b 0 the b 0, b 0.. (i) b if b 0 (ii) (iii) (iv) b if b b if either b or b b if

More information

Inner Product Spaces (Chapter 5)

Inner Product Spaces (Chapter 5) Ier Product Spces Chpter 5 I this chpter e ler out :.Orthogol ectors orthogol suspces orthogol mtrices orthogol ses. Proectios o ectors d o suspces Orthogol Suspces We ko he ectors re orthogol ut ht out

More information

Addendum. Addendum. Vector Review. Department of Computer Science and Engineering 1-1

Addendum. Addendum. Vector Review. Department of Computer Science and Engineering 1-1 Addedum Addedum Vetor Review Deprtmet of Computer Siee d Egieerig - Coordite Systems Right hded oordite system Addedum y z Deprtmet of Computer Siee d Egieerig - -3 Deprtmet of Computer Siee d Egieerig

More information

A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD

A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD Diol Bgoo () A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD I. Itroductio The first seprtio of vribles (see pplictios to Newto s equtios) is ver useful method

More information

Unit 1. Extending the Number System. 2 Jordan School District

Unit 1. Extending the Number System. 2 Jordan School District Uit Etedig the Number System Jord School District Uit Cluster (N.RN. & N.RN.): Etedig Properties of Epoets Cluster : Etedig properties of epoets.. Defie rtiol epoets d eted the properties of iteger epoets

More information

Lecture 2. Rational Exponents and Radicals. 36 y. b can be expressed using the. Rational Exponent, thus b. b can be expressed using the

Lecture 2. Rational Exponents and Radicals. 36 y. b can be expressed using the. Rational Exponent, thus b. b can be expressed using the Lecture. Rtiol Epoets d Rdicls Rtiol Epoets d Rdicls Lier Equtios d Iequlities i Oe Vrile Qudrtic Equtios Appedi A6 Nth Root - Defiitio Rtiol Epoets d Rdicls For turl umer, c e epressed usig the r is th

More information

Limit of a function:

Limit of a function: - Limit of fuctio: We sy tht f ( ) eists d is equl with (rel) umer L if f( ) gets s close s we wt to L if is close eough to (This defiitio c e geerlized for L y syig tht f( ) ecomes s lrge (or s lrge egtive

More information

MATRIX ALGEBRA, Systems Linear Equations

MATRIX ALGEBRA, Systems Linear Equations MATRIX ALGEBRA, Systes Lier Equtios Now we chge to the LINEAR ALGEBRA perspective o vectors d trices to reforulte systes of lier equtios. If you fid the discussio i ters of geerl d gets lost i geerlity,

More information

Vectors. Vectors in Plane ( 2

Vectors. Vectors in Plane ( 2 Vectors Vectors i Ple ( ) The ide bout vector is to represet directiol force Tht mes tht every vector should hve two compoets directio (directiol slope) d mgitude (the legth) I the ple we preset vector

More information

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case Chpter : Algebr: A. Bckgroud lgebr: A. Like ters: I lgebric expressio of the for: () x b y c z x y o z d x... p x.. we cosider x, y, z to be vribles d, b, c, d,,, o,.. to be costts. I lgebric expressio

More information

Simpson s 1/3 rd Rule of Integration

Simpson s 1/3 rd Rule of Integration Simpso s 1/3 rd Rule o Itegrtio Mjor: All Egieerig Mjors Authors: Autr Kw, Chrlie Brker Trsormig Numericl Methods Eductio or STEM Udergrdutes 1/10/010 1 Simpso s 1/3 rd Rule o Itegrtio Wht is Itegrtio?

More information

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2 Mth 3, Clculus II Fil Exm Solutios. (5 poits) Use the limit defiitio of the defiite itegrl d the sum formuls to compute 3 x + x. Check your swer by usig the Fudmetl Theorem of Clculus. Solutio: The limit

More information

Surds, Indices, and Logarithms Radical

Surds, Indices, and Logarithms Radical MAT 6 Surds, Idices, d Logrithms Rdicl Defiitio of the Rdicl For ll rel, y > 0, d ll itegers > 0, y if d oly if y where is the ide is the rdicl is the rdicd. Surds A umber which c be epressed s frctio

More information

Autar Kaw Benjamin Rigsby. Transforming Numerical Methods Education for STEM Undergraduates

Autar Kaw Benjamin Rigsby.   Transforming Numerical Methods Education for STEM Undergraduates Autr Kw Bejmi Rigsby http://m.mthforcollege.com Trsformig Numericl Methods Eductio for STEM Udergrdutes http://m.mthforcollege.com . solve set of simulteous lier equtios usig Nïve Guss elimitio,. ler the

More information

lecture 16: Introduction to Least Squares Approximation

lecture 16: Introduction to Least Squares Approximation 97 lecture 16: Itroductio to Lest Squres Approximtio.4 Lest squres pproximtio The miimx criterio is ituitive objective for pproximtig fuctio. However, i my cses it is more ppelig (for both computtio d

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digitl Sigl Processig, Fll 6 Lecture 6: Sstem structures for implemettio Zeg-u T Deprtmet of Electroic Sstems Alorg Uiversit, Demr t@om.u.d Digitl Sigl Processig, VI, Zeg-u T, 6 Course t glce Discrete-time

More information

Northwest High School s Algebra 2

Northwest High School s Algebra 2 Northwest High School s Algebr Summer Review Pcket 0 DUE August 8, 0 Studet Nme This pcket hs bee desiged to help ou review vrious mthemticl topics tht will be ecessr for our success i Algebr. Istructios:

More information

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Dr. Hamid R. Rabiee Fall 2013 Sigls & Systems Chpter 0: The Z-Trsform Adpted from: Lecture otes from MIT, Bighmto Uiversity Dr. Hmid R. Rbiee Fll 03 Lecture 5 Chpter 0 Lecture 6 Chpter 0 Outlie Itroductio to the -Trsform Properties

More information

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory

SM2H. Unit 2 Polynomials, Exponents, Radicals & Complex Numbers Notes. 3.1 Number Theory SMH Uit Polyomils, Epoets, Rdicls & Comple Numbers Notes.1 Number Theory .1 Addig, Subtrctig, d Multiplyig Polyomils Notes Moomil: A epressio tht is umber, vrible, or umbers d vribles multiplied together.

More information

ALGEBRA II CHAPTER 7 NOTES. Name

ALGEBRA II CHAPTER 7 NOTES. Name ALGEBRA II CHAPTER 7 NOTES Ne Algebr II 7. th Roots d Rtiol Expoets Tody I evlutig th roots of rel ubers usig both rdicl d rtiol expoet ottio. I successful tody whe I c evlute th roots. It is iportt for

More information

Fourier Series and Applications

Fourier Series and Applications 9/7/9 Fourier Series d Applictios Fuctios epsio is doe to uderstd the better i powers o etc. My iportt probles ivolvig prtil dieretil equtios c be solved provided give uctio c be epressed s iiite su o

More information

Unit 1 Chapter-3 Partial Fractions, Algebraic Relationships, Surds, Indices, Logarithms

Unit 1 Chapter-3 Partial Fractions, Algebraic Relationships, Surds, Indices, Logarithms Uit Chpter- Prtil Frctios, Algeric Reltioships, Surds, Idices, Logriths. Prtil Frctios: A frctio of the for 7 where the degree of the uertor is less th the degree of the deoitor is referred to s proper

More information

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS A GENERALIZATION OF GAU THEOREM ON QUADRATIC FORM Nicole I Brtu d Adi N Cret Deprtmet of Mth - Criov Uiversity, Romi ABTRACT A origil result cocerig the extesio of Guss s theorem from the theory of biry

More information

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1.

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1. GRAPHING LINEAR EQUATIONS Qudrt II Qudrt I ORDERED PAIR: The first umer i the ordered pir is the -coordite d the secod umer i the ordered pir is the y-coordite. (, ) Origi ( 0, 0 ) _-is Lier Equtios Qudrt

More information

Frequency-domain Characteristics of Discrete-time LTI Systems

Frequency-domain Characteristics of Discrete-time LTI Systems requecy-domi Chrcteristics of Discrete-time LTI Systems Prof. Siripog Potisuk LTI System descriptio Previous bsis fuctio: uit smple or DT impulse The iput sequece is represeted s lier combitio of shifted

More information

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form 0.5 Power Series I the lst three sectios, we ve spet most of tht time tlkig bout how to determie if series is coverget or ot. Now it is time to strt lookig t some specific kids of series d we will evetully

More information

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication Next. Covered bsics of simple desig techique (Divided-coquer) Ch. of the text.. Next, Strsse s lgorithm. Lter: more desig d coquer lgorithms: MergeSort. Solvig recurreces d the Mster Theorem. Similr ide

More information

Linear Programming. Preliminaries

Linear Programming. Preliminaries Lier Progrmmig Prelimiries Optimiztio ethods: 3L Objectives To itroduce lier progrmmig problems (LPP To discuss the stdrd d coicl form of LPP To discuss elemetry opertio for lier set of equtios Optimiztio

More information

Advanced Algorithmic Problem Solving Le 6 Math and Search

Advanced Algorithmic Problem Solving Le 6 Math and Search Advced Algorithmic Prolem Solvig Le Mth d Serch Fredrik Heitz Dept of Computer d Iformtio Sciece Liköpig Uiversity Outlie Arithmetic (l. d.) Solvig lier equtio systems (l. d.) Chiese remider theorem (l.5

More information

Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006

Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006 Sttistics for Ficil Egieerig Sessio : Lier Algebr Review rch 8 th, 6 Topics Itroductio to trices trix opertios Determits d Crmer s rule Eigevlues d Eigevectors Quiz The cotet of Sessio my be fmilir to

More information

The total number of permutations of S is n!. We denote the set of all permutations of S by

The total number of permutations of S is n!. We denote the set of all permutations of S by DETERMINNTS. DEFINITIONS Def: Let S {,,, } e the set of itegers from to, rrged i scedig order. rerrgemet jjj j of the elemets of S is clled permuttio of S. S. The totl umer of permuttios of S is!. We deote

More information

Chapter 7 Infinite Series

Chapter 7 Infinite Series MA Ifiite Series Asst.Prof.Dr.Supree Liswdi Chpter 7 Ifiite Series Sectio 7. Sequece A sequece c be thought of s list of umbers writte i defiite order:,,...,,... 2 The umber is clled the first term, 2

More information

Linford 1. Kyle Linford. Math 211. Honors Project. Theorems to Analyze: Theorem 2.4 The Limit of a Function Involving a Radical (A4)

Linford 1. Kyle Linford. Math 211. Honors Project. Theorems to Analyze: Theorem 2.4 The Limit of a Function Involving a Radical (A4) Liford 1 Kyle Liford Mth 211 Hoors Project Theorems to Alyze: Theorem 2.4 The Limit of Fuctio Ivolvig Rdicl (A4) Theorem 2.8 The Squeeze Theorem (A5) Theorem 2.9 The Limit of Si(x)/x = 1 (p. 85) Theorem

More information

(200 terms) equals Let f (x) = 1 + x + x 2 + +x 100 = x101 1

(200 terms) equals Let f (x) = 1 + x + x 2 + +x 100 = x101 1 SECTION 5. PGE 78.. DMS: CLCULUS.... 5. 6. CHPTE 5. Sectio 5. pge 78 i + + + INTEGTION Sums d Sigm Nottio j j + + + + + i + + + + i j i i + + + j j + 5 + + j + + 9 + + 7. 5 + 6 + 7 + 8 + 9 9 i i5 8. +

More information

(II.G) PRIME POWER MODULI AND POWER RESIDUES

(II.G) PRIME POWER MODULI AND POWER RESIDUES II.G PRIME POWER MODULI AND POWER RESIDUES I II.C, we used the Chiese Remider Theorem to reduce cogrueces modulo m r i i to cogrueces modulo r i i. For exmles d roblems, we stuck with r i 1 becuse we hd

More information

PROGRESSIONS AND SERIES

PROGRESSIONS AND SERIES PROGRESSIONS AND SERIES A sequece is lso clled progressio. We ow study three importt types of sequeces: () The Arithmetic Progressio, () The Geometric Progressio, () The Hrmoic Progressio. Arithmetic Progressio.

More information

DIGITAL SIGNAL PROCESSING LECTURE 5

DIGITAL SIGNAL PROCESSING LECTURE 5 DIGITAL SIGNAL PROCESSING LECTURE 5 Fll K8-5 th Semester Thir Muhmmd tmuhmmd_7@yhoo.com Cotet d Figures re from Discrete-Time Sigl Processig, e by Oppeheim, Shfer, d Buck, 999- Pretice Hll Ic. The -Trsform

More information

The Exponential Function

The Exponential Function The Epoetil Fuctio Defiitio: A epoetil fuctio with bse is defied s P for some costt P where 0 d. The most frequetly used bse for epoetil fuctio is the fmous umber e.788... E.: It hs bee foud tht oyge cosumptio

More information

Eigenfunction Expansion. For a given function on the internal a x b the eigenfunction expansion of f(x):

Eigenfunction Expansion. For a given function on the internal a x b the eigenfunction expansion of f(x): Eigefuctio Epsio: For give fuctio o the iterl the eigefuctio epsio of f(): f ( ) cmm( ) m 1 Eigefuctio Epsio (Geerlized Fourier Series) To determie c s we multiply oth sides y Φ ()r() d itegrte: f ( )

More information

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning Hdout # Title: FAE Course: Eco 8/ Sprig/5 Istructor: Dr I-Mig Chiu Itroductio to Mtrix: Mtrix opertios & Geometric meig Mtrix: rectgulr rry of umers eclosed i pretheses or squre rckets It is covetiolly

More information

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1 Appedix A.. Itroductio As discussed i the Chpter 9 o Sequeces d Series, sequece,,...,,... hvig ifiite umber of terms is clled ifiite sequece d its idicted sum, i.e., + + +... + +... is clled ifite series

More information

Numbers (Part I) -- Solutions

Numbers (Part I) -- Solutions Ley College -- For AMATYC SML Mth Competitio Cochig Sessios v.., [/7/00] sme s /6/009 versio, with presettio improvemets Numbers Prt I) -- Solutios. The equtio b c 008 hs solutio i which, b, c re distict

More information

11/16/2010 The Inner Product.doc 1/9. The Inner Product. So we now know that a continuous, analog signal v t can be expressed as:

11/16/2010 The Inner Product.doc 1/9. The Inner Product. So we now know that a continuous, analog signal v t can be expressed as: 11/16/2010 The Ier Product.doc 1/9 The Ier Product So we ow kow tht cotiuous, log sigl v t c be epressed s: v t t So tht cotiuous, log sigl c be (lmost) completel specified b discrete set of umbers:,,,,,,

More information

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Hamid R. Rabiee Arman Sepehr Fall 2010

Chapter 10: The Z-Transform Adapted from: Lecture notes from MIT, Binghamton University Hamid R. Rabiee Arman Sepehr Fall 2010 Sigls & Systems Chpter 0: The Z-Trsform Adpted from: Lecture otes from MIT, Bighmto Uiversity Hmid R. Riee Arm Sepehr Fll 00 Lecture 5 Chpter 0 Outlie Itroductio to the -Trsform Properties of the ROC of

More information

Merge Sort. Outline and Reading. Divide-and-Conquer. Divide-and-conquer paradigm ( 4.1.1) Merge-sort ( 4.1.1)

Merge Sort. Outline and Reading. Divide-and-Conquer. Divide-and-conquer paradigm ( 4.1.1) Merge-sort ( 4.1.1) Merge Sort 7 2 9 4 2 4 7 9 7 2 2 7 9 4 4 9 7 7 2 2 9 9 4 4 Merge Sort versio 1.3 1 Outlie d Redig Divide-d-coquer prdigm ( 4.1.1 Merge-sort ( 4.1.1 Algorithm Mergig two sorted sequeces Merge-sort tree

More information

Mu Alpha Theta National Convention: Denver, 2001 Sequences & Series Topic Test Alpha Division

Mu Alpha Theta National Convention: Denver, 2001 Sequences & Series Topic Test Alpha Division Mu Alph Thet Ntiol Covetio: Dever, 00 Sequeces & Series Topic Test Alph Divisio. Wht is the commo rtio of the geometric sequece, 7, 9,? 7 (C) 5. The commo differece of the rithmetic sequece,, 0, is 5 (C)

More information

Orthogonality, orthogonalization, least squares

Orthogonality, orthogonalization, least squares ier Alger for Wireless Commuictios ecture: 3 Orthogolit, orthogoliztio, lest squres Ier products d Cosies he gle etee o-zero vectors d is cosθθ he l of Cosies: + cosθ If the gle etee to vectors is π/ (90º),

More information

MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE

MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE Prt 1. Let be odd rime d let Z such tht gcd(, 1. Show tht if is qudrtic residue mod, the is qudrtic residue mod for y ositive iteger.

More information

ECE 102 Engineering Computation

ECE 102 Engineering Computation ECE Egieerig Computtio Phillip Wog Mth Review Vetor Bsis Mtri Bsis System of Lier Equtios Summtio Symol is the symol for summtio. Emple: N k N... 9 k k k k k the, If e e e f e f k Vetor Bsis A vetor is

More information

Content: Essential Calculus, Early Transcendentals, James Stewart, 2007 Chapter 1: Functions and Limits., in a set B.

Content: Essential Calculus, Early Transcendentals, James Stewart, 2007 Chapter 1: Functions and Limits., in a set B. Review Sheet: Chpter Cotet: Essetil Clculus, Erly Trscedetls, Jmes Stewrt, 007 Chpter : Fuctios d Limits Cocepts, Defiitios, Lws, Theorems: A fuctio, f, is rule tht ssigs to ech elemet i set A ectly oe

More information

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11 UTCLIFFE NOTE: CALCULU WOKOWKI CHAPTER Ifiite eries Coverget or Diverget eries Cosider the sequece If we form the ifiite sum 0, 00, 000, 0 00 000, we hve wht is clled ifiite series We wt to fid the sum

More information

Basic Maths. Fiorella Sgallari University of Bologna, Italy Faculty of Engineering Department of Mathematics - CIRAM

Basic Maths. Fiorella Sgallari University of Bologna, Italy Faculty of Engineering Department of Mathematics - CIRAM Bsic Mths Fiorell Sgllri Uiversity of Bolog, Itly Fculty of Egieerig Deprtmet of Mthemtics - CIRM Mtrices Specil mtrices Lier mps Trce Determits Rk Rge Null spce Sclr products Norms Mtri orms Positive

More information

Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials

Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials Numericl Solutios of Fredholm Itegrl Equtios Usig erstei Polyomils A. Shiri, M. S. Islm Istitute of Nturl Scieces, Uited Itertiol Uiversity, Dhk-, gldesh Deprtmet of Mthemtics, Uiversity of Dhk, Dhk-,

More information

MA123, Chapter 9: Computing some integrals (pp )

MA123, Chapter 9: Computing some integrals (pp ) MA13, Chpter 9: Computig some itegrls (pp. 189-05) Dte: Chpter Gols: Uderstd how to use bsic summtio formuls to evlute more complex sums. Uderstd how to compute its of rtiol fuctios t ifiity. Uderstd how

More information

Discrete Mathematics I Tutorial 12

Discrete Mathematics I Tutorial 12 Discrete Mthemtics I Tutoril Refer to Chpter 4., 4., 4.4. For ech of these sequeces fid recurrece reltio stisfied by this sequece. (The swers re ot uique becuse there re ifiitely my differet recurrece

More information

Section 6.3: Geometric Sequences

Section 6.3: Geometric Sequences 40 Chpter 6 Sectio 6.: Geometric Sequeces My jobs offer ul cost-of-livig icrese to keep slries cosistet with ifltio. Suppose, for exmple, recet college grdute fids positio s sles mger erig ul slry of $6,000.

More information

( a n ) converges or diverges.

( a n ) converges or diverges. Chpter Ifiite Series Pge of Sectio E Rtio Test Chpter : Ifiite Series By the ed of this sectio you will be ble to uderstd the proof of the rtio test test series for covergece by pplyig the rtio test pprecite

More information

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields Lecture 38 (Trpped Prticles) Physics 6-01 Sprig 018 Dougls Fields Free Prticle Solutio Schrödiger s Wve Equtio i 1D If motio is restricted to oe-dimesio, the del opertor just becomes the prtil derivtive

More information

Numerical Methods (CENG 2002) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. In this chapter, we will deal with the case of determining the values of x 1

Numerical Methods (CENG 2002) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. In this chapter, we will deal with the case of determining the values of x 1 Numericl Methods (CENG 00) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. Itroductio I this chpter, we will del with the cse of determiig the vlues of,,..., tht simulteously stisfy the set of equtios: f f...

More information

2.1.1 Definition The Z-transform of a sequence x [n] is simply defined as (2.1) X re x k re x k r

2.1.1 Definition The Z-transform of a sequence x [n] is simply defined as (2.1) X re x k re x k r Z-Trsforms. INTRODUCTION TO Z-TRANSFORM The Z-trsform is coveiet d vluble tool for represetig, lyig d desigig discrete-time sigls d systems. It plys similr role i discrete-time systems to tht which Lplce

More information

Week 13 Notes: 1) Riemann Sum. Aim: Compute Area Under a Graph. Suppose we want to find out the area of a graph, like the one on the right:

Week 13 Notes: 1) Riemann Sum. Aim: Compute Area Under a Graph. Suppose we want to find out the area of a graph, like the one on the right: Week 1 Notes: 1) Riem Sum Aim: Compute Are Uder Grph Suppose we wt to fid out the re of grph, like the oe o the right: We wt to kow the re of the red re. Here re some wys to pproximte the re: We cut the

More information

Appendix A Examples for Labs 1, 2, 3 1. FACTORING POLYNOMIALS

Appendix A Examples for Labs 1, 2, 3 1. FACTORING POLYNOMIALS Appedi A Emples for Ls,,. FACTORING POLYNOMIALS Tere re m stdrd metods of fctorig tt ou ve lered i previous courses. You will uild o tese fctorig metods i our preclculus course to ele ou to fctor epressios

More information

Approximate Integration

Approximate Integration Study Sheet (7.7) Approimte Itegrtio I this sectio, we will ler: How to fid pproimte vlues of defiite itegrls. There re two situtios i which it is impossile to fid the ect vlue of defiite itegrl. Situtio:

More information

Exponents and Radical

Exponents and Radical Expoets d Rdil Rule : If the root is eve d iside the rdil is egtive, the the swer is o rel umber, meig tht If is eve d is egtive, the Beuse rel umber multiplied eve times by itself will be lwys positive.

More information

Elementary Linear Algebra

Elementary Linear Algebra Elemetry Lier Alger Ato & Rorres, th Editio Lecture Set Chpter : Systems of Lier Equtios & Mtrices Chpter Cotets Itroductio to System of Lier Equtios Gussi Elimitio Mtrices d Mtri Opertios Iverses; Rules

More information

Pre-Calculus - Chapter 3 Sections Notes

Pre-Calculus - Chapter 3 Sections Notes Pre-Clculus - Chpter 3 Sectios 3.1-3.4- Notes Properties o Epoets (Review) 1. ( )( ) = + 2. ( ) =, (c) = 3. 0 = 1 4. - = 1/( ) 5. 6. c Epoetil Fuctios (Sectio 3.1) Deiitio o Epoetil Fuctios The uctio deied

More information

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS) Mthemtics Revisio Guides Itegrtig Trig, Log d Ep Fuctios Pge of MK HOME TUITION Mthemtics Revisio Guides Level: AS / A Level AQA : C Edecel: C OCR: C OCR MEI: C INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

More information

National Quali cations AHEXEMPLAR PAPER ONLY

National Quali cations AHEXEMPLAR PAPER ONLY Ntiol Quli ctios AHEXEMPLAR PAPER ONLY EP/AH/0 Mthemtics Dte Not pplicble Durtio hours Totl mrks 00 Attempt ALL questios. You my use clcultor. Full credit will be give oly to solutios which coti pproprite

More information

Supplemental Handout #1. Orthogonal Functions & Expansions

Supplemental Handout #1. Orthogonal Functions & Expansions UIUC Physics 435 EM Fields & Sources I Fll Semester, 27 Supp HO # 1 Prof. Steve Errede Supplemetl Hdout #1 Orthogol Fuctios & Epsios Cosider fuctio f ( ) which is defied o the itervl. The fuctio f ( )

More information

Important Facts You Need To Know/Review:

Important Facts You Need To Know/Review: Importt Fcts You Need To Kow/Review: Clculus: If fuctio is cotiuous o itervl I, the its grph is coected o I If f is cotiuous, d lim g Emple: lim eists, the lim lim f g f g d lim cos cos lim 3 si lim, t

More information

Student Success Center Elementary Algebra Study Guide for the ACCUPLACER (CPT)

Student Success Center Elementary Algebra Study Guide for the ACCUPLACER (CPT) Studet Success Ceter Elemetry Algebr Study Guide for the ACCUPLACER (CPT) The followig smple questios re similr to the formt d cotet of questios o the Accuplcer Elemetry Algebr test. Reviewig these smples

More information

The Definite Riemann Integral

The Definite Riemann Integral These otes closely follow the presettio of the mteril give i Jmes Stewrt s textook Clculus, Cocepts d Cotexts (d editio). These otes re iteded primrily for i-clss presettio d should ot e regrded s sustitute

More information

Chapter Real Numbers

Chapter Real Numbers Chpter. - Rel Numbers Itegers: coutig umbers, zero, d the egtive of the coutig umbers. ex: {,-3, -, -,,,, 3, } Rtiol Numbers: quotiets of two itegers with ozero deomitor; termitig or repetig decimls. ex:

More information

is an ordered list of numbers. Each number in a sequence is a term of a sequence. n-1 term

is an ordered list of numbers. Each number in a sequence is a term of a sequence. n-1 term Mthemticl Ptters. Arithmetic Sequeces. Arithmetic Series. To idetify mthemticl ptters foud sequece. To use formul to fid the th term of sequece. To defie, idetify, d pply rithmetic sequeces. To defie rithmetic

More information

1.3 Continuous Functions and Riemann Sums

1.3 Continuous Functions and Riemann Sums mth riem sums, prt 0 Cotiuous Fuctios d Riem Sums I Exmple we sw tht lim Lower() = lim Upper() for the fuctio!! f (x) = + x o [0, ] This is o ccidet It is exmple of the followig theorem THEOREM Let f be

More information

Review of the Riemann Integral

Review of the Riemann Integral Chpter 1 Review of the Riem Itegrl This chpter provides quick review of the bsic properties of the Riem itegrl. 1.0 Itegrls d Riem Sums Defiitio 1.0.1. Let [, b] be fiite, closed itervl. A prtitio P of

More information

Module Summary Sheets. FP1, Further Concepts for Advanced Mathematics

Module Summary Sheets. FP1, Further Concepts for Advanced Mathematics MEI Mthemtics i Eductio d Idustry MEI Structured Mthemtics Module Summry Sheets FP, Further Cocepts for Advced Mthemtics Topic : Mtrices Topic : Comple Numbers Topic : Curve Sketchig Topic 4: Algebr Purchsers

More information

Assessment Center Elementary Algebra Study Guide for the ACCUPLACER (CPT)

Assessment Center Elementary Algebra Study Guide for the ACCUPLACER (CPT) Assessmet Ceter Elemetr Alger Stud Guide for the ACCUPLACER (CPT) The followig smple questios re similr to the formt d cotet of questios o the Accuplcer Elemetr Alger test. Reviewig these smples will give

More information

LEVEL I. ,... if it is known that a 1

LEVEL I. ,... if it is known that a 1 LEVEL I Fid the sum of first terms of the AP, if it is kow tht + 5 + 0 + 5 + 0 + = 5 The iterior gles of polygo re i rithmetic progressio The smllest gle is 0 d the commo differece is 5 Fid the umber of

More information

Chapter 2 Infinite Series Page 1 of 9

Chapter 2 Infinite Series Page 1 of 9 Chpter Ifiite eries Pge of 9 Chpter : Ifiite eries ectio A Itroductio to Ifiite eries By the ed of this sectio you will be ble to uderstd wht is met by covergece d divergece of ifiite series recogise geometric

More information

y udv uv y v du 7.1 INTEGRATION BY PARTS

y udv uv y v du 7.1 INTEGRATION BY PARTS 7. INTEGRATION BY PARTS Ever differetitio rule hs correspodig itegrtio rule. For istce, the Substitutio Rule for itegrtio correspods to the Chi Rule for differetitio. The rule tht correspods to the Product

More information

Next we encountered the exponent equaled 1, so we take a leap of faith and generalize that for any x (that s not zero),

Next we encountered the exponent equaled 1, so we take a leap of faith and generalize that for any x (that s not zero), 79 CH 0 MORE EXPONENTS Itroductio T his chpter is cotiutio of the epoet ides we ve used m times efore. Our gol is to comie epressios with epoets i them. First, quick review of epoets: 0 0 () () 0 ( ) 0

More information

MATH 174: Numerical Analysis. Lecturer: Jomar F. Rabajante 1 st Sem AY

MATH 174: Numerical Analysis. Lecturer: Jomar F. Rabajante 1 st Sem AY MATH 74: Numeric Aysis Lecturer: Jomr F. Rbjte st Sem AY - INTERPOLATION THEORY We wt to seect fuctio p from give css of fuctios i such wy tht the grph of y=p psses through fiite set of give dt poits odes.

More information

Numerical Integration

Numerical Integration Numericl tegrtio Newto-Cotes Numericl tegrtio Scheme Replce complicted uctio or tulted dt with some pproimtig uctio tht is esy to itegrte d d 3-7 Roerto Muscedere The itegrtio o some uctios c e very esy

More information

Closed Newton-Cotes Integration

Closed Newton-Cotes Integration Closed Newto-Cotes Itegrtio Jmes Keeslig This documet will discuss Newto-Cotes Itegrtio. Other methods of umericl itegrtio will be discussed i other posts. The other methods will iclude the Trpezoidl Rule,

More information

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Divide-and-Conquer

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Divide-and-Conquer Presettio for use with the textook, Algorithm Desig d Applictios, y M. T. Goodrich d R. Tmssi, Wiley, 25 Divide-d-Coquer Divide-d-Coquer Divide-d coquer is geerl lgorithm desig prdigm: Divide: divide the

More information

2a a a 2a 4a. 3a/2 f(x) dx a/2 = 6i) Equation of plane OAB is r = λa + µb. Since C lies on the plane OAB, c can be expressed as c = λa +

2a a a 2a 4a. 3a/2 f(x) dx a/2 = 6i) Equation of plane OAB is r = λa + µb. Since C lies on the plane OAB, c can be expressed as c = λa + -6-5 - - - - 5 6 - - - - - - / GCE A Level H Mths Nov Pper i) z + z 6 5 + z 9 From GC, poit of itersectio ( 8, 9 6, 5 ). z + z 6 5 9 From GC, there is o solutio. So p, q, r hve o commo poits of itersectio.

More information