Orthogonal Functions. Orthogonal Series Expansion. Orthonormal Functions. Page 1. Orthogonal Functions and Fourier Series. (x)dx = 0.

Size: px
Start display at page:

Download "Orthogonal Functions. Orthogonal Series Expansion. Orthonormal Functions. Page 1. Orthogonal Functions and Fourier Series. (x)dx = 0."

Transcription

1 Orthogol Fuctios q Th ir roduct of two fuctios f d f o itrvl [, ] is th umr Orthogol Fuctios d Fourir Sris ( f, f ) f f dx. q Two fuctios f d f r sid to orthogol o itrvl [, ] if ( f, f ) f f dx. q A st of rl-vlud fuctios {φ, φ, φ, } is sid to orthogol st o itrvl [, ] if (ϕ m,ϕ ) ϕ m ϕ dx, m. q Exmls: Th st {, cos x, cos x, } o th itrvl [-π, π] is orthogol. 7 Orthoorml Fuctios q Th orm or grlizd lgth of fuctio is dfid s ϕ (ϕ,ϕ ) ϕ dx. q A st of orthogol fuctios {φ, φ, φ, } tht r ormlizd y thir orms is clld orthoorml st.!# ϕ ϕ, ϕ ϕ, ϕ $# ϕ,! %# & # q Suos {φ } is ifiit orthogol st of fuctios o itrvl [, ] d yf is fuctio dfid o this itrvl. Th, whr Orthogol Sris Exsio f q This is clld orthogol sris xsio of f. ϕ, f ϕ dx, ϕ q Exmls: Th st o th itrvl [-π, π] is orthogol. { / π,cos x / π, cosx / π,!} 8 9 Pg

2 Orthogol Fuctios with Wight Fuctio q A st of rl-vlud fuctios {φ, φ, φ, } is sid to orthogol with rsct to wight fuctio w o itrvl [, ] if wϕ m ϕ dx, m. q Suos {φ } is ifiit orthogol st of fuctios o itrvl [, ] d yf is fuctio dfid o this itrvl. Th, whr q This is clld orthogol sris xsio of f. f ϕ, f wϕ dx, ϕ ϕ wϕ dx. q Th st of trigoomtric fuctios π π 3π π π 3π,cos x,cos x,cos x,!,si x,si x,si x,! is orthogol o th itrvl [-, ]. q Th Fourir sris of fuctio f dfid o th itrvl (-, ) is giv y Fourir Sris f +! # cos π x + si π x $ & % f dx, f cos π x dx, f si π x dx Covrgc of Fourir Sris q Lt f d f icwis cotiuous o th itrvl (-, ); tht is f d f cotiuous xct t fiit umr of oits i th itrvl d hv oly fiit discotiuity t ths oits. q Th Fourir sris of f o th itrvl covrgs to f t oit of cotiuity. q At oit of discotiuity, th Fourir sris covrgs to th vrg [ f (x + )+f (x - )]/ whr f (x + ) d f (x - ) dot th limit of f t x from th right d from th lft, rsctivly. Clss Exrcis q Fid d lot Fourir sris of #%, π / < x < f $ &% cos x, x < π / π π / π / cos x dx π cos x cosx dx ( )+ π π (4 ) π / 4 cos xsix dx π π (4 ) f π + # ( ) + π (4 ) cosx + 4 % $ π (4 ) six & ( 3 Pg

3 Ev d Odd Fuctios q A fuctio f is sid to v if f (-x) f d odd if f (-x) - f. q Th roduct of two v fuctios is v. q Th roduct of two odd fuctios is v. q Th roduct of v fuctio d odd fuctio is odd. q Th sum (diffrc) of two v fuctios is v. q Th sum (diffrc) of two odd fuctios is odd. q If f is v, th f dx f dx. q If f is odd, th f dx. Fourir Cosi d Si Sris q Th Fourir sris of v fuctio f dfid o th itrvl (-, ) is cosi sris giv y f + cos π x f dx, f cos π x dx q Th Fourir sris of odd fuctio f dfid o th itrvl (-, ) is si sris giv y f si π x f si π x dx 4 5 q Eulr s Formul: For rl umr x ix q Solvig for cos x d si x givs q Sustitutig ito Fourir sris of fuctio f dfid o itrvl (-, ) rsults i comlx Fourir sris of this fuctio. Comlx Fourir Sris cos x + isi x cos x ix + ix f ix si x iπ x/ cos x isi x ix i ix f iπ x/ dx,,±,±,! 6 Fourir Sris d Frqucy Sctrum q Fourir sris of fuctio o th itrvl (-, ) dfis riodic fuctio with th fudmtl riod of T. q If w dfi ωπ / T s th fudmtl gulr frqucy, th Fourir sris com f ( x) + q Th lot of oits (ω, ) is clld frqucy sctrum of f. cos ω x + si ωx d f ( x) c iωx 7 Pg 3

4 Clss Exrcis q Fid comlx Fourir sris d frqucy sctrum of $ f # %$ ( ), πi c f ( ) πi iπ x/, < x <, < x < Sturm-Liouvill Prolm q Lt, q, r, d r rl-vlud fuctios cotiuous o itrvl [, ], d lt r > d > for vry x i th itrvl. Th, d [ r( x) y ] + ( q( x) + λ( x) ) y dx A y( ) + B y( ) A y( ) + B is sid to rgulr Sturm-Liouvill Prolm. q Exml: Lgdrs Equtio : ( x y( ) ) y xy + ( + ) y 8 9 Prortis of Rgulr Sturm-Liouvill Prolm q Thr xist ifiit umr of rl igvlus tht c rrgd i scdig ordr λ < λ < λ 3 < < λ such tht λ s. q For ch igvlu thr is oly o igfuctio. q Eigfuctios corrsodig to diffrt igvlus r lirly iddt. q Th st of igfuctios corrsodig to th st of igvlus is orthogol with rsct to th wight fuctio o th itrvl [, ]. Covrsio to Slf-Adjoit Form q Evry scod-ordr diffrtil qutio y+ y+ c + λd c covrtd to th so clld slf-djoit form y dividig th origil qutio y d multilyig y q Exml: Prmtric Bssl Equtio x y+ xy+ (α x v d )y dx [xy]+ # α & % x v (y $ x ( ) y d dx ry [ ] + q+ λ ( ) y (/)dx Pg 4

5 x Bssl Fuctios r Orthogol q Th rmtric Bssl qutio d y + xy + ( α x ) y [ xy] + α x y dx x hs two solutios J (αx) d Y (αx) ut oly J (αx) is oudd t x. q Th st [J x)] is orthogol with rsct to th wight fuctio x o itrvl [, ]; xj x)j (α j x)dx, α i α j. q α i r giv y oudry coditio t x ; A J ( α) + BαJ ( α). Diffrtil Rcurrc Rltios d! dx x J # $ x J d! dx x J # $ x J + or xj J xj + xj xj J 3 q Th orthogol sris xsio of fuctio f dfid o th itrvl [, ] i trms of Bssl fuctios, whr Fourir-Bssl Sris f c i J x), c i i xj x) f dx, J x) Lgdr s Fuctios r Orthogol q Th Lgdr olyomils, which r th solutios of th Lgdr s qutio ( x ) y xy + ( + ) y, r orthogol with rsct to th wight fuctio o th itrvl [-, ]; P m P dx, m. d th squr orm of th fuctio J x) is dfid y J x) xj x)dx. 4 5 Pg 5

6 q Th orthogol sris xsio of fuctio f dfid o th itrvl [-, ] i trms of Lgdr fuctios, whr Fourir-Lgdr Sris f P, P f dx, P d th squr orm of th fuctio P is dfid y P + 6 Pg 6

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

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

Power Means Calculus Product Calculus, Harmonic Mean Calculus, and Quadratic Mean Calculus

Power Means Calculus Product Calculus, Harmonic Mean Calculus, and Quadratic Mean Calculus Gug Istitut Jourl, Volum 4, No 4, Novmbr 008 H. Vic Do Powr Ms Clculus Product Clculus, Hrmoic M Clculus, d Qudrtic M Clculus H. Vic Do vick@dc.com Mrch, 008 Gug Istitut Jourl, Volum 4, No 4, Novmbr 008

More information

Problem Set 6 Solutions

Problem Set 6 Solutions 6.04/18.06J Mathmatics for Computr Scic March 15, 005 Srii Dvadas ad Eric Lhma Problm St 6 Solutios Du: Moday, March 8 at 9 PM Problm 1. Sammy th Shar is a fiacial srvic providr who offrs loas o th followig

More information

A New Approach on Smarandache tn 1 Curves in terms of Spacelike Biharmonic Curves with a Timelike Binormal in the Lorentzian Heisenberg Group Heis 3

A New Approach on Smarandache tn 1 Curves in terms of Spacelike Biharmonic Curves with a Timelike Binormal in the Lorentzian Heisenberg Group Heis 3 Jourl of Vctoril Rltivity JVR 6 (0) 8-5 A Nw Approch o Smrdch t Curvs i trms of Spclik Bihrmoic Curvs with Timlik Biorml i th Lortzi Hisbrg Group His T Körpir d E Turh ABSTRACT: I this ppr, w study spclik

More information

SOME IMPORTANT MATHEMATICAL FORMULAE

SOME IMPORTANT MATHEMATICAL FORMULAE SOME IMPORTANT MATHEMATICAL FORMULAE Circle : Are = π r ; Circuferece = π r Squre : Are = ; Perieter = 4 Rectgle: Are = y ; Perieter = (+y) Trigle : Are = (bse)(height) ; Perieter = +b+c Are of equilterl

More information

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

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

More information

AC Circuits Three-Phase Circuits

AC Circuits Three-Phase Circuits AC Circuits Thr-Phs Circuits Contnts Wht is Thr-Phs Circuit? Blnc Thr-Phs oltgs Blnc Thr-Phs Connction Powr in Blncd Systm Unblncd Thr-Phs Systms Aliction Rsidntil Wiring Sinusoidl voltg sourcs A siml

More information

New Basis Functions. Section 8. Complex Fourier Series

New Basis Functions. Section 8. Complex Fourier Series Nw Basis Functions Sction 8 Complx Fourir Sris Th complx Fourir sris is prsntd first with priod 2, thn with gnral priod. Th connction with th ral-valud Fourir sris is xplaind and formula ar givn for convrting

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

4.3. The Integral and Comparison Tests

4.3. The Integral and Comparison Tests 4.3. THE INTEGRAL AND COMPARISON TESTS 9 4.3. The Itegral ad Compariso Tests 4.3.. The Itegral Test. Suppose f is a cotiuous, positive, decreasig fuctio o [, ), ad let a = f(). The the covergece or divergece

More information

Chapter 3 Chemical Equations and Stoichiometry

Chapter 3 Chemical Equations and Stoichiometry Chptr Chmicl Equtions nd Stoichiomtry Homwork (This is VERY importnt chptr) Chptr 27, 29, 1, 9, 5, 7, 9, 55, 57, 65, 71, 75, 77, 81, 87, 91, 95, 99, 101, 111, 117, 121 1 2 Introduction Up until now w hv

More information

MATHEMATICS SYLLABUS SECONDARY 7th YEAR

MATHEMATICS SYLLABUS SECONDARY 7th YEAR Europe Schools Office of the Secretry-Geerl Pedgogicl developmet Uit Ref.: 2011-01-D-41-e-2 Orig.: DE MATHEMATICS SYLLABUS SECONDARY 7th YEAR Stdrd level 5 period/week course Approved y the Joit Techig

More information

PROBLEMS 05 - ELLIPSE Page 1

PROBLEMS 05 - ELLIPSE Page 1 PROBLEMS 0 ELLIPSE Pge 1 ( 1 ) The edpoits A d B of AB re o the X d Yis respectivel If AB > 0 > 0 d P divides AB from A i the rtio : the show tht P lies o the ellipse 1 ( ) If the feet of the perpediculrs

More information

Overview of some probability distributions.

Overview of some probability distributions. Lecture Overview of some probability distributios. I this lecture we will review several commo distributios that will be used ofte throughtout the class. Each distributio is usually described by its probability

More information

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993

Schedule C. Notice in terms of Rule 5(10) of the Capital Gains Rules, 1993 (Rul 5(10)) Shul C Noti in trms o Rul 5(10) o th Cpitl Gins Ruls, 1993 Sttmnt to sumitt y trnsror o shrs whr thr is trnsr o ontrolling intrst Prt 1 - Dtils o Trnsror Nm Arss ROC No (ompnis only) Inom Tx

More information

Heat (or Diffusion) equation in 1D*

Heat (or Diffusion) equation in 1D* Heat (or Diffusio) equatio i D* Derivatio of the D heat equatio Separatio of variables (refresher) Worked eamples *Kreysig, 8 th Ed, Sectios.4b Physical assumptios We cosider temperature i a log thi wire

More information

Convexity, Inequalities, and Norms

Convexity, Inequalities, and Norms Covexity, Iequalities, ad Norms Covex Fuctios You are probably familiar with the otio of cocavity of fuctios. Give a twicedifferetiable fuctio ϕ: R R, We say that ϕ is covex (or cocave up) if ϕ (x) 0 for

More information

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t Homework Solutios. Chater, Sectio 7, Problem 56. Fid the iverse Lalace trasform of the fuctio F () (7.6). À Chater, Sectio 7, Problem 6. Fid the iverse Lalace trasform of the fuctio F () usig (7.6). Solutio:

More information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

More information

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

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

More information

Exponential Generating Functions

Exponential Generating Functions Epotl Grtg Fuctos COS 3 Dscrt Mthmtcs Epotl Grtg Fuctos (,,, ) : squc of rl umbrs Epotl Grtg fucto of ths squc s th powr srs ( )! 3 Ordry Grtg Fuctos (,,, ) : squc of rl umbrs Ordry Grtg Fucto of ths squc

More information

Chapter 04.05 System of Equations

Chapter 04.05 System of Equations hpter 04.05 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

UNIVERSITETET I OSLO

UNIVERSITETET I OSLO NIVERSITETET I OSLO Det matematisk-naturvitenskapelige fakultet Examination in: Trial exam Partial differential equations and Sobolev spaces I. Day of examination: November 18. 2009. Examination hours:

More information

Lecture 5: Span, linear independence, bases, and dimension

Lecture 5: Span, linear independence, bases, and dimension Lecture 5: Spa, liear idepedece, bases, ad dimesio Travis Schedler Thurs, Sep 23, 2010 (versio: 9/21 9:55 PM) 1 Motivatio Motivatio To uderstad what it meas that R has dimesio oe, R 2 dimesio 2, etc.;

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

Question 3: How do you find the relative extrema of a function?

Question 3: How do you find the relative extrema of a function? ustion 3: How do you find th rlativ trma of a function? Th stratgy for tracking th sign of th drivativ is usful for mor than dtrmining whr a function is incrasing or dcrasing. It is also usful for locating

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Basic Elements of Arithmetic Sequences and Series

Basic Elements of Arithmetic Sequences and Series MA40S PRE-CALCULUS UNIT G GEOMETRIC SEQUENCES CLASS NOTES (COMPLETED NO NEED TO COPY NOTES FROM OVERHEAD) Basic Elemets of Arithmetic Sequeces ad Series Objective: To establish basic elemets of arithmetic

More information

On the L p -conjecture for locally compact groups

On the L p -conjecture for locally compact groups Arch. Math. 89 (2007), 237 242 c 2007 Birkhäuser Verlag Basel/Switzerlad 0003/889X/030237-6, ublished olie 2007-08-0 DOI 0.007/s0003-007-993-x Archiv der Mathematik O the L -cojecture for locally comact

More information

Batteries in general: Batteries. Anode/cathode in rechargeable batteries. Rechargeable batteries

Batteries in general: Batteries. Anode/cathode in rechargeable batteries. Rechargeable batteries Bttris i grl: Bttris How -bsd bttris work A rducig (gtiv) lctrod A oxidizig (positiv) lctrod A - th ioic coductor Rchrgbl bttris Rctios ust b rvrsibl Not too y irrvrsibl sid rctios Aod/cthod i rchrgbl

More information

Higher. Exponentials and Logarithms 160

Higher. Exponentials and Logarithms 160 hsn uknt Highr Mthmtics UNIT UTCME Eponntils nd Logrithms Contnts Eponntils nd Logrithms 6 Eponntils 6 Logrithms 6 Lws of Logrithms 6 Eponntils nd Logrithms to th Bs 65 5 Eponntil nd Logrithmic Equtions

More information

Partial Di erential Equations

Partial Di erential Equations Partial Di eretial Equatios Partial Di eretial Equatios Much of moder sciece, egieerig, ad mathematics is based o the study of partial di eretial equatios, where a partial di eretial equatio is a equatio

More information

THE EFFECT OF GROUND SETTLEMENTS ON THE AXIAL RESPONSE OF PILES: SOME CLOSED FORM SOLUTIONS CUED/D-SOILS/TR 341 (Aug 2005) By A. Klar and K.

THE EFFECT OF GROUND SETTLEMENTS ON THE AXIAL RESPONSE OF PILES: SOME CLOSED FORM SOLUTIONS CUED/D-SOILS/TR 341 (Aug 2005) By A. Klar and K. THE EFFECT OF GROUND SETTEMENTS ON THE AXIA RESPONSE OF PIES: SOME COSED FORM SOUTIONS CUED/D-SOIS/TR 4 Aug 5 By A. Klr d K. Sog Klr d Sog "Th Effct of Groud Displcmt o Axil Rspos of Pils: Som Closd Form

More information

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

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? JÖRG JAHNEL 1. My Motivatio Some Sort of a Itroductio Last term I tought Topological Groups at the Göttige Georg August Uiversity. This

More information

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE ENGINEEING FO UL DEVELOENT Jelgv, 28.-29.05.2009. INVESTIGTION OF ETES OF CCUULTO TNSISSION OF SELF- OVING CHINE leksdrs Kirk Lithui Uiversity of griculture, Kus leksdrs.kirk@lzuu.lt.lt bstrct. Uder the

More information

Section 8.3 : De Moivre s Theorem and Applications

Section 8.3 : De Moivre s Theorem and Applications The Sectio 8 : De Moivre s Theorem ad Applicatios Let z 1 ad z be complex umbers, where z 1 = r 1, z = r, arg(z 1 ) = θ 1, arg(z ) = θ z 1 = r 1 (cos θ 1 + i si θ 1 ) z = r (cos θ + i si θ ) ad z 1 z =

More information

x o R n a π(a, x o ) A R n π(a, x o ) π(a, x o ) A R n a a x o x o x n X R n δ(x n, x o ) d(a, x n ) d(, ) δ(, ) R n x n X d(a, x n ) δ(x n, x o ) a = a A π(a, xo ) a a A = X = R π(a, x o ) = (x o + ρ)

More information

Harold s Calculus Notes Cheat Sheet 26 April 2016

Harold s Calculus Notes Cheat Sheet 26 April 2016 Hrol s Clculus Notes Chet Sheet 26 April 206 AP Clculus Limits Defiitio of Limit Let f e fuctio efie o ope itervl cotiig c let L e rel umer. The sttemet: lim x f(x) = L mes tht for ech ε > 0 there exists

More information

Maximum Likelihood Estimators.

Maximum Likelihood Estimators. Lecture 2 Maximum Likelihood Estimators. Matlab example. As a motivatio, let us look at oe Matlab example. Let us geerate a radom sample of size 00 from beta distributio Beta(5, 2). We will lear the defiitio

More information

Fundamentals of Tensor Analysis

Fundamentals of Tensor Analysis MCEN 503/ASEN 50 Chptr Fundmntls of Tnsor Anlysis Fll, 006 Fundmntls of Tnsor Anlysis Concpts of Sclr, Vctor, nd Tnsor Sclr α Vctor A physicl quntity tht cn compltly dscrid y rl numr. Exmpl: Tmprtur; Mss;

More information

Outline. Binary Tree

Outline. Binary Tree Outlin Similrity Srh Th Nikolus Augstn Fr Univrsity of Bozn-Bolzno Fulty of Computr Sin DIS 1 Binry Rprsnttion of Tr Binry Brnhs Lowr Boun for th Eit Distn Unit 10 My 17, 2012 Nikolus Augstn (DIS) Similrity

More information

1. MATHEMATICAL INDUCTION

1. MATHEMATICAL INDUCTION 1. MATHEMATICAL INDUCTION EXAMPLE 1: Prove that for ay iteger 1. Proof: 1 + 2 + 3 +... + ( + 1 2 (1.1 STEP 1: For 1 (1.1 is true, sice 1 1(1 + 1. 2 STEP 2: Suppose (1.1 is true for some k 1, that is 1

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Wireless Communication Technologies

Wireless Communication Technologies Wirlss Commuicatio chologis Rutgrs Uivrsity Dpt. of Elctrical ad Computr Egirig ECE559 (Advacd opics i Commuicatio Egirig Lctur & (Fruary 7 & March 4, Istructor: Dr. araya B. Madayam Summary y Di Wu (diwu@wila.rutgrs.du

More information

Chapter 10 Function of a Matrix

Chapter 10 Function of a Matrix EE448/58 Vrsion. John Stnsby Chatr Function of a atrix t f(z) b a comlx-valud function of a comlx variabl z. t A b an n n comlxvalud matrix. In this chatr, w giv a dfinition for th n n matrix f(a). Also,

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

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

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 74 (4 ) Chapter 4 Sequeces ad Series 4. SEQUENCES I this sectio Defiitio Fidig a Formula for the th Term The word sequece is a familiar word. We may speak of a sequece of evets or say that somethig is

More information

Application: Volume. 6.1 Overture. Cylinders

Application: Volume. 6.1 Overture. Cylinders Applictio: Volume 61 Overture I this chpter we preset other pplictio of the defiite itegrl, this time to fid volumes of certi solids As importt s this prticulr pplictio is, more importt is to recogize

More information

Auburn University Style Guide & Identification Standards Manual

Auburn University Style Guide & Identification Standards Manual y E k H PM 28 C 9 C MY M y K v B 10 k 0% : 60 64 % % x 11 C M MY Y K v 6 97 1% : % P PM 17 C 2 M MY Y K v 6 88 6% : % P PM 15 8 PM 17 2 B R G ID E & PM ID P E 15 8 T IC IF T IO PM 17 2 D T R D M L 0 0

More information

Fast Fourier Transform

Fast Fourier Transform 18.310 lecture otes November 18, 2013 Fast Fourier Trasform Lecturer: Michel Goemas I these otes we defie the Discrete Fourier Trasform, ad give a method for computig it fast: the Fast Fourier Trasform.

More information

Building Blocks Problem Related to Harmonic Series

Building Blocks Problem Related to Harmonic Series TMME, vol3, o, p.76 Buildig Blocks Problem Related to Harmoic Series Yutaka Nishiyama Osaka Uiversity of Ecoomics, Japa Abstract: I this discussio I give a eplaatio of the divergece ad covergece of ifiite

More information

Euler s Formula Math 220

Euler s Formula Math 220 Euler s Formula Math 0 last change: Sept 3, 05 Complex numbers A complex number is an expression of the form x+iy where x and y are real numbers and i is the imaginary square root of. For example, + 3i

More information

Metric, Normed, and Topological Spaces

Metric, Normed, and Topological Spaces Chapter 13 Metric, Normed, ad Topological Spaces A metric space is a set X that has a otio of the distace d(x, y) betwee every pair of poits x, y X. A fudametal example is R with the absolute-value metric

More information

ELASTIC MODULII AND THEIR RELATIONSHIP BY CONSIDERING ANY ARBITRARY ANGLE

ELASTIC MODULII AND THEIR RELATIONSHIP BY CONSIDERING ANY ARBITRARY ANGLE Itratioal Joural of Mchaical girig ad Tcholog (IJMT Volum 7, Issu, March-April 016, pp. 33-38, Articl ID: IJMT_07_0_004 Availabl oli at http://www.iam.com/ijmt/issus.asp?jtp=ijmt&vtp=7&itp= Joural Impact

More information

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6

Reading. Minimum Spanning Trees. Outline. A File Sharing Problem. A Kevin Bacon Problem. Spanning Trees. Section 9.6 Rin Stion 9.6 Minimum Spnnin Trs Outlin Minimum Spnnin Trs Prim s Alorithm Kruskl s Alorithm Extr:Distriut Shortst-Pth Alorithms A Fil Shrin Prolm Sy unh o usrs wnt to istriut il monst thmslvs. Btwn h

More information

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

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4 GCE Further Mathematics (660) Further Pure Uit (MFP) Tetbook Versio: 4 MFP Tetbook A-level Further Mathematics 660 Further Pure : Cotets Chapter : Comple umbers 4 Itroductio 5 The geeral comple umber 5

More information

Review: Classification Outline

Review: Classification Outline Data Miig CS 341, Sprig 2007 Decisio Trees Neural etworks Review: Lecture 6: Classificatio issues, regressio, bayesia classificatio Pretice Hall 2 Data Miig Core Techiques Classificatio Clusterig Associatio

More information

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

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006 Exam format UC Bereley Departmet of Electrical Egieerig ad Computer Sciece EE 6: Probablity ad Radom Processes Solutios 9 Sprig 006 The secod midterm will be held o Wedesday May 7; CHECK the fial exam

More information

Math 113 HW #11 Solutions

Math 113 HW #11 Solutions Math 3 HW # Solutios 5. 4. (a) Estimate the area uder the graph of f(x) = x from x = to x = 4 usig four approximatig rectagles ad right edpoits. Sketch the graph ad the rectagles. Is your estimate a uderestimate

More information

APPLICATION NOTE 30 DFT or FFT? A Comparison of Fourier Transform Techniques

APPLICATION NOTE 30 DFT or FFT? A Comparison of Fourier Transform Techniques APPLICATION NOTE 30 DFT or FFT? A Compariso of Fourier Trasform Techiques This applicatio ote ivestigates differeces i performace betwee the DFT (Discrete Fourier Trasform) ad the FFT(Fast Fourier Trasform)

More information

Solutions to Practice Problems for Test 4

Solutions to Practice Problems for Test 4 olutions to Practice Problems for Test 4 1. Let be the line segmentfrom the point (, 1, 1) to the point (,, 3). Evaluate the line integral y ds. Answer: First, we parametrize the line segment from (, 1,

More information

A Fuzzy Inventory System with Deteriorating Items under Supplier Credits Linked to Ordering Quantity

A Fuzzy Inventory System with Deteriorating Items under Supplier Credits Linked to Ordering Quantity JOURNAL OF INFORMAION SCIENCE AND ENGINEERING 6, 3-53 () A Fuzzy Ivtory Syst with Dtrioratig Its udr Supplir Crdits Likd to Ordrig Quatity LIANG-YUH OUYANG, JINN-SAIR ENG AND MEI-CHUAN CHENG 3 Dpartt of

More information

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

Factoring x n 1: cyclotomic and Aurifeuillian polynomials Paul Garrett <garrett@math.umn.edu> (March 16, 004) Factorig x 1: cyclotomic ad Aurifeuillia polyomials Paul Garrett Polyomials of the form x 1, x 3 1, x 4 1 have at least oe systematic factorizatio x 1 = (x 1)(x 1

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

Ďě Ž ť č ď ť ď ú ď ť ě Ě ň Ě ě ú ň ž ú ú Ú ú ú Ě ň é é ž ú ž Ť Ť Ť ú ň Ď ú ň ď Ě ú É ž ř ú ě ň ý Ě ň ý ň ň Ť ř ď ř ň ú Ť ě ř ě ý Š Ú Ú ň ň ú Ó Ú ň Ň Ů ž ú ň Č ř ř ú É ě ň ú Ž ý ú ú Ú Ú ť ž ž ď ý ž ď ž

More information

Parameter estimation for nonlinear models: Numerical approaches to solving the inverse problem. Lecture 11 04/01/2008. Sven Zenker

Parameter estimation for nonlinear models: Numerical approaches to solving the inverse problem. Lecture 11 04/01/2008. Sven Zenker Parameter estimatio for oliear models: Numerical approaches to solvig the iverse problem Lecture 11 04/01/2008 Sve Zeker Review: Trasformatio of radom variables Cosider probability distributio of a radom

More information

Permutations, the Parity Theorem, and Determinants

Permutations, the Parity Theorem, and Determinants 1 Permutatios, the Parity Theorem, ad Determiats Joh A. Guber Departmet of Electrical ad Computer Egieerig Uiversity of Wiscosi Madiso Cotets 1 What is a Permutatio 1 2 Cycles 2 2.1 Traspositios 4 3 Orbits

More information

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A RAJALAKSHMI ENGINEERING COLLEGE MA 26 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS. Solve (D 2 + D 2)y = 0. 2. Solve (D 2 + 6D + 9)y = 0. PART A 3. Solve (D 4 + 4)x = 0 where D = d dt 4. Find Particular Integral:

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Sometimes functions are given not in the form y = f(x) but in a more complicated form in which it is difficult or impossible to express y explicitly in terms of x. Such functions

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Chapter 9 SEQUENCES AND SERIES Natural umbers are the product of huma spirit. DEDEKIND 9.1 Itroductio I mathematics, the word, sequece is used i much the same way as it is i ordiary Eglish. Whe we say

More information

The one dimensional heat equation: Neumann and Robin boundary conditions

The one dimensional heat equation: Neumann and Robin boundary conditions The one dimensional heat equation: Neumann and Robin boundary conditions Ryan C. Trinity University Partial Differential Equations February 28, 2012 with Neumann boundary conditions Our goal is to solve:

More information

The Binomial Multi- Section Transformer

The Binomial Multi- Section Transformer 4/15/21 The Bioial Multisectio Matchig Trasforer.doc 1/17 The Bioial Multi- Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where: Γ ( ω

More information

Research Article Sign Data Derivative Recovery

Research Article Sign Data Derivative Recovery Iteratioal Scholarly Research Network ISRN Applied Mathematics Volume 0, Article ID 63070, 7 pages doi:0.540/0/63070 Research Article Sig Data Derivative Recovery L. M. Housto, G. A. Glass, ad A. D. Dymikov

More information

Institute of Actuaries of India Subject CT1 Financial Mathematics

Institute of Actuaries of India Subject CT1 Financial Mathematics Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i

More information

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

Math 114- Intermediate Algebra Integral Exponents & Fractional Exponents (10 ) Math 4 Math 4- Itermediate Algebra Itegral Epoets & Fractioal Epoets (0 ) Epoetial Fuctios Epoetial Fuctios ad Graphs I. Epoetial Fuctios The fuctio f ( ) a, where is a real umber, a 0, ad a, is called

More information

AP Calculus BC 2003 Scoring Guidelines Form B

AP Calculus BC 2003 Scoring Guidelines Form B AP Calculus BC Scorig Guidelies Form B The materials icluded i these files are iteded for use by AP teachers for course ad exam preparatio; permissio for ay other use must be sought from the Advaced Placemet

More information

Calculus 1: Sample Questions, Final Exam, Solutions

Calculus 1: Sample Questions, Final Exam, Solutions Calculus : Sample Questions, Final Exam, Solutions. Short answer. Put your answer in the blank. NO PARTIAL CREDIT! (a) (b) (c) (d) (e) e 3 e Evaluate dx. Your answer should be in the x form of an integer.

More information

Lecture 27. Rectangular Metal Waveguides

Lecture 27. Rectangular Metal Waveguides Lctu 7 Rctgul Mtl Wvguids I this lctu u will l: Rctgul tl wvguids T d TM guidd ds i ctgul tl wvguids C 303 Fll 006 Fh R Cll Uivsit Plll Plt Mtl Wvguids d 1 T Mds: Dispsi lti: ( ) si { 1,, d d d 1 TM Mds:

More information

Systems with Persistent Memory: the Observation Inequality Problems and Solutions

Systems with Persistent Memory: the Observation Inequality Problems and Solutions Chapter 6 Systems with Persistent Memory: the Observation Inequality Problems and Solutions Facts that are recalled in the problems wt) = ut) + 1 c A 1 s ] R c t s)) hws) + Ks r)wr)dr ds. 6.1) w = w +

More information

1 The Gaussian channel

1 The Gaussian channel ECE 77 Lecture 0 The Gaussia chael Objective: I this lecture we will lear about commuicatio over a chael of practical iterest, i which the trasmitted sigal is subjected to additive white Gaussia oise.

More information

Hybrid Neural Network/Modal Method Modeling of Uniaxial Waveguide Discontinuities

Hybrid Neural Network/Modal Method Modeling of Uniaxial Waveguide Discontinuities 70 NTERNTONL JOURNL OF MCROWVE ND OPTCL TECHNOLOGY, VOL.6, NO., MRCH 0 Hyrid Neural Networ/Modal Method Modelig of Uiaxial Waveguide Discotiuities M. Yahia* +#, J. W. Tao, H. Bezia #3, M. N. delrim +#4

More information

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

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 The followig eample will help us uderstad The Samplig Distributio of the Mea Review: The populatio is the etire collectio of all idividuals or objects of iterest The sample is the portio of the populatio

More information

A Note on Approximating. the Normal Distribution Function

A Note on Approximating. the Normal Distribution Function Applid Mathmatical Scincs, Vol, 00, no 9, 45-49 A Not on Approimating th Normal Distribution Function K M Aludaat and M T Alodat Dpartmnt of Statistics Yarmouk Univrsity, Jordan Aludaatkm@hotmailcom and

More information

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

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

Lecture 20: Emitter Follower and Differential Amplifiers

Lecture 20: Emitter Follower and Differential Amplifiers Whits, EE 3 Lctur 0 Pag of 8 Lctur 0: Emittr Followr and Diffrntial Amplifirs Th nxt two amplifir circuits w will discuss ar ry important to lctrical nginring in gnral, and to th NorCal 40A spcifically.

More information

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1355 - INTERMEDIATE ALGEBRA I (3 CREDIT HOURS)

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1355 - INTERMEDIATE ALGEBRA I (3 CREDIT HOURS) SINCLAIR COMMUNITY COLLEGE DAYTON OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1355 - INTERMEDIATE ALGEBRA I (3 CREDIT HOURS) 1. COURSE DESCRIPTION: Ftorig; opertios with polyoils d rtiol expressios; solvig

More information

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

MATH 425, PRACTICE FINAL EXAM SOLUTIONS. MATH 45, PRACTICE FINAL EXAM SOLUTIONS. Exercise. a Is the operator L defined on smooth functions of x, y by L u := u xx + cosu linear? b Does the answer change if we replace the operator L by the operator

More information

Sample Problems. Practice Problems

Sample Problems. Practice Problems Lecture Notes Partial Fractions page Sample Problems Compute each of the following integrals.. x dx. x + x (x + ) (x ) (x ) dx 8. x x dx... x (x + ) (x + ) dx x + x x dx x + x x + 6x x dx + x 6. 7. x (x

More information

http://www.webassign.net/v4cgijeff.downs@wnc/control.pl

http://www.webassign.net/v4cgijeff.downs@wnc/control.pl Assigmet Previewer http://www.webassig.et/vcgijeff.dows@wc/cotrol.pl of // : PM Practice Eam () Questio Descriptio Eam over chapter.. Questio DetailsLarCalc... [] Fid the geeral solutio of the differetial

More information

2.2 Separable Equations

2.2 Separable Equations 2.2 Separable Equations 73 2.2 Separable Equations An equation y = f(x, y) is called separable provided algebraic operations, usually multiplication, division and factorization, allow it to be written

More information

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of Queueig Theory INTRODUCTION Queueig theory dels with the study of queues (witig lies). Queues boud i rcticl situtios. The erliest use of queueig theory ws i the desig of telehoe system. Alictios of queueig

More information

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture

Distributed Systems Principles and Paradigms. Chapter 11: Distributed File Systems. Distributed File Systems. Example: NFS Architecture Distriut Systms Prinipls n Prigms Mrtn vn Stn VU mstrm, Dpt. Computr Sin stn@s.vu.nl Chptr 11: Vrsion: Dmr 10, 2012 1 / 14 Gnrl gol Try to mk fil systm trnsprntly vill to rmot lints. 1. Fil mov to lint

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

2-3 The Remainder and Factor Theorems

2-3 The Remainder and Factor Theorems - The Remaider ad Factor Theorems Factor each polyomial completely usig the give factor ad log divisio 1 x + x x 60; x + So, x + x x 60 = (x + )(x x 15) Factorig the quadratic expressio yields x + x x

More information

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5 Sectio 13 Kolmogorov-Smirov test. Suppose that we have a i.i.d. sample X 1,..., X with some ukow distributio P ad we would like to test the hypothesis that P is equal to a particular distributio P 0, i.e.

More information