23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

Size: px
Start display at page:

Download "23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes"

Transcription

1 Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals involving sinusoids. We hen assume ha if f() is a periodic funcion, of period, hen he Fourier series expansion akes he form: f() = a + (a n cos n + b n sin n) Our main purpose here is o show how he consans in his expansion, a n (for n =,,, 3... and b n (for n =,, 3,... ), may be deermined for any given funcion f(). Prerequisies Before saring his Secion you should... Learning Oucomes On compleion you should be able o... know wha a periodic funcion is be able o inegrae funcions involving sinusoids have knowledge of inegraion by pars calculae Fourier coefficiens of a funcion of period calculae Fourier coefficiens of a funcion of general period HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 9

2 . Inroducion We recall firs a simple rigonomeric ideniy: cos = + cos or equivalenly cos = + cos () Equaion can be inerpreed as a simple finie Fourier series represenaion of he periodic funcion f() = cos which has period. We noe ha he Fourier series represenaion conains a consan erm and a period erm. A more complicaed rigonomeric ideniy is sin 4 = 3 8 cos + cos 4 () 8 which again can be considered as a finie Fourier series represenaion. (Do no worry if you are unfamiliar wih he resul ().) Noe ha he funcion f() = sin 4 (which has period ) is being wrien in erms of a consan funcion, a funcion of period or frequency (he firs harmonic ) and a funcion of period or frequency (he second harmonic ). The reason for he consan erm in boh () and () is ha each of he funcions cos and sin 4 is non-negaive and hence each mus have a posiive average value. Any sinusoid of he form cos n or sin n has, by symmery, zero average value. Therefore, so would a Fourier series conaining only such erms. A consan erm can herefore be expeced o arise in he Fourier series of a funcion which has a non-zero average value.. Funcions of period We now discuss how o represen periodic non-sinusoidal funcions f() of period in erms of sinusoids, i.e. how o obain Fourier series represenaions. As already discussed we expec such Fourier series o conain harmonics of frequency n (n =,, 3,...) and, if he periodic funcion has a non-zero average value, a consan erm. Thus we seek a Fourier series represenaion of he general form f() = a + a cos + a cos b sin + b sin +... The reason for labelling he consan erm as a will be discussed laer. The ampliudes a, a,... b, b,... of he sinusoids are called Fourier coefficiens. Obaining he Fourier coefficiens for a given periodic funcion f() is our main ask and is referred o as Fourier Analysis. Before embarking on such an analysis i is insrucive o esablish, a leas qualiaively, he plausibiliy of approximaing a funcion by a few erms of is Fourier series. HELM (8): Workbook 3: Fourier Series

3 Task Consider he square wave of period one period of which is shown in Figure. 4 (a) Wrie down he analyic descripion of his funcion, (b) Sae wheher you expec he Fourier series of his funcion o conain a consan erm, (c) Lis any oher possible feaures of he Fourier series ha you migh expec from he graph of he square-wave funcion. Your soluion (a) We have f() = f( + ) = f() 4 < < < <, < < (b) The Fourier series will conain a consan erm since he square wave here is non-negaive and canno herefore have a zero average value. This consan erm is ofen referred o as he d.c. (direc curren) erm by engineers. (c) Since he square wave is an even funcion (i.e. he graph has symmery abou he y axis) hen is Fourier series will conain cosine erms bu no sine erms because only he cosines are even funcions. (Well done if you spoed his a his early sage!) HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series

4 I is possible o show, and we will do so laer, ha he Fourier series represenaion of his square wave is + 8 {cos 3 cos cos 5 7 } cos i.e. he Fourier coefficiens are a =, a = 8, a =, a 3 = 8 3, a 4 =, a 5 = 8 5,... Noe, as well as he presence of he consan erm and of he cosine (bu no sine) erms, ha only odd harmonics are presen i.e. sinusoids of period, 3, 5,,... or of frequency, 3, 5, 7,... 7 imes he fundamenal frequency. We now show in Figure 8 graphs of (i) he square wave (ii) he firs wo erms of he Fourier series represening he square wave (iii) he firs hree erms of he Fourier series represening he square wave (iv) he firs four erms of he Fourier series represening he square wave (v) he firs five erms of he Fourier series represening he square wave Noe: We show he graphs for < < only since he square wave and is Fourier series are even. (i) 4 (ii) (iii) + 8 cos + 8 (cos cos 3 ) (iv) + 8 (v) (cos 3 cos cos 5 ) (cos 3 cos cos 5 cos 7 ) Figure 8 HELM (8): Workbook 3: Fourier Series

5 We can clearly see from Figure 8 ha as he number of erms is increased he graph of he Fourier series gradually approaches ha of he original square wave - he ripples increase in number bu decrease in ampliude. (The behaviour near he disconinuiy, a =, is slighly more complicaed and i is possible o show ha however many erms are aken in he Fourier series, some overshoo will always occur. This effec, which we do no discuss furher, is known as he Gibbs Phenomenon.) Orhogonaliy properies of sinusoids As saed earlier, a periodic funcion f() wih period has a Fourier series represenaion f() = a + a cos + a cos b sin + b sin +..., = a + (a n cos n + b n sin n) (3) To deermine he Fourier coefficiens a n, b n and he consan erm a use has o be made of cerain inegrals involving sinusoids, he inegrals being over a range α, α +, where α is any number. (We will normally choose α =.) Task Find sin n d and cos n d where n is an ineger. Your soluion In fac boh inegrals are zero for [ sin n d = ] n cos n = ( cos n + cos n) = n n (4) cos n d = [ ] sin n = n (5) n As special cases, if n = he firs inegral is zero and he second inegral has value. N.B. Any inegraion range α, α +, would give hese same (zero) answers. These inegrals enable us o calculae he consan erm in he Fourier series (3) as in he following ask. HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 3

6 Task Inegrae boh sides of (3) from o and use he resuls from he previous Task. Hence obain an expression for a. Your soluion We ge for he lef-hand side f()d (whose value clearly depends on he funcion f()). Inegraing he righ-hand side erm by erm we ge { } a d + a n cos n d + b n sin n d = (using he inegrals (4) and (5) shown above). Thus we ge f() d = (a ) or a = [ ] a + { + } f() d (6) Key Poin The consan erm in a rigonomeric Fourier series for a funcion of period is a = f() d = average value of f() over period. 4 HELM (8): Workbook 3: Fourier Series

7 This resul ies in wih our earlier discussion on he significance of he consan erm. Clearly a signal whose average value is zero will have no consan erm in is Fourier series. The following square wave (Figure 9) is an example. f() Figure 9 We now obain furher inegrals, known as orhogonaliy properies, which enable us o find he remaining Fourier coefficiens i.e. he ampliudes a n and b n (n =,, 3,...) of he sinusoids. Task Using he sandard rigonomeric ideniy ha sin n cos m {sin(n + m) + sin(n m)} evaluae sin n cos m d where n and m are any inegers. Your soluion We ge sin n cos m d = { sin(n + m) d + using he resuls (4) and (5) since n + m and n m are also inegers. This resul holds for any inerval of. } sin(n m) d = { + } = HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 5

8 Key Poin Orhogonaliy Relaion For any inegers m, n, including he case m = n, sin n cos m d = We shall use his resul shorly bu need a few more inegrals firs. Consider nex cos n cos m d where m and n are inegers. Using anoher rigonomeric ideniy we have, for he case n m, cos n cos m d = {cos(n + m) + cos(n m)}d = { + } = using he inegrals (4) and (5). For he case n = m we mus ge a non-zero answer since cos n is non-negaive. In his case: cos n d = = ( + cos n) d [ + sin n n ] = ( provided n ) For he case n = m = we have cos n cos m d = Task Proceeding in a similar way o he above, evaluae sin n sin m d for inegers m and n. Again consider separaely he hree cases: (a) n m, (b) n = m and (c) n = m =. 6 HELM (8): Workbook 3: Fourier Series

9 Your soluion (a) Using he ideniy sin n sin m {cos(n m) cos(n + m)} and inegraing he righhand side erms, we ge, using (4) and (5) sin n sin m d = n, m inegers n m (b) Using he ideniy cos θ = sin θ wih θ = n gives for n = m (c) When n = m =, sin n d = sin n sin m d =. We summarise hese resuls in he following Key Poin: ( cos n)d = For inegers n, m Key Poin 3 sin n cos m d = cos n cos m d = sin n sin m d = n m n = m n = m = { n m, n = m = n = m All hese resuls hold for any inegraion range of widh. HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 7

10 3. Calculaion of Fourier coefficiens Consider he Fourier series for a funcion f() of period : f() = a + (a n cos n + b n sin n) (7) To obain he coefficiens a n (n =,, 3,...), we muliply boh sides by cos m where m is some posiive ineger and inegrae boh sides from o. For he lef-hand side we obain f() cos m d For he righ-hand side we obain a cos m d + {a n cos n cos m d + b n The firs inegral is zero using (5). } sin n cos m d Using he orhogonaliy relaions all he inegrals in he summaion give zero excep for he case n = m when, from Key Poin 3 cos m d = Hence f() cos m d = a m from which he coefficien a m can be obained. Rewriing m as n we ge a n = f() cos n d for n =,, 3,... (8) Using (6), we see he formula also works for n = (bu we mus remember ha he consan erm is a.) From (8) a n = average value of f() cos n over one period. 8 HELM (8): Workbook 3: Fourier Series

11 Task By muliplying (7) by sin m obain an expression for he Fourier Sine coefficiens b n, n =,, 3,... Your soluion A similar calculaion o ha performed o find he a n gives f() sin m d = a sin m d + { a n cos n sin m d + All erms on he righ-hand side inegrae o zero excep for he case n = m where b m sin m d = b m Relabelling m as n gives b n = } b n sin n sin m d f() sin n d n =,, 3,... (9) (There is no Fourier coefficien b.) Clearly b n = average value of f() sin n over one period. HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 9

12 Key Poin 4 A funcion f() wih period has a Fourier series f() = a + (a n cos n + b n sin n) The Fourier coefficiens are a n = b n = f() cos n d n =,,,... f() sin n d n =,,... In he inegrals any convenien inegraion range exending over an inerval of may be used. 4. Examples of Fourier series We shall obain he Fourier series of he half-recified square wave shown in Figure. f() period We have Figure f() = f( + ) = f() { < < < < The calculaion of he Fourier coefficiens is merely sraighforward inegraion using he resuls already obained: a n = f() cos n d in general. Hence, for our square wave a n = () cos n d = [ sin n n ] = provided n HELM (8): Workbook 3: Fourier Series

13 Bu a = () d = so he consan erm is a =. (The square wave akes on values and over equal lengh inervals of so value.) Similarly b n = () sin n d = Some care is needed now! b n = ( cos n) n Bu cos n = + n =, 4, 6,..., [ ] cos n n is clearly he mean b n = n =, 4, 6,... However, cos n = n =, 3, 5,... b n = ( ( )) = n n i.e. b =, b 3 = 3, b 5 = 5,... Hence he required Fourier series is n =, 3, 5,... f() = a + (a n cos n + b n sin n) in general f() = + (sin + 3 sin sin ) in his case Noe ha he Fourier series for his paricular form of he square wave conains a consan erm and odd harmonic sine erms. We already know why he consan erm arises (because of he non-zero mean value of he funcions) and will explain laer why he presence of any odd harmonic sine erms could have been prediced wihou inegraion. The Fourier series we have found can be wrien in summaion noaion in various ways: + (n odd) Fourier series as sin n or, since n is odd, we may wrie n = k k =,,... and wrie he n + k= sin(k ) (k ) HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series

14 Task Obain he Fourier series of he square wave one period of which is shown: 4 Your soluion HELM (8): Workbook 3: Fourier Series

15 We have, since he funcion is non-zero only for < <, a = 4 d = 4 a = is he consan erm as we would expec. Also a n = = 4 n { sin 4 cos n d = 4 ( n } [ sin n n ( sin n )) ] = 8 n sin ( n I follows from a knowledge of he sine funcion ha n =, 4, 6,... ) n =,, 3,... Also a n = b n = 8 n 8 n n =, 5, 9,... n = 3, 7,,... 4 sin n d = 4 [ ] cos n n = 4 { ( n cos n Hence, he required Fourier series is f() = + 8 (cos 3 cos cos 5 7 ) cos ) ( cos n )} = which, like he previous square wave, conains a consan erm and odd harmonics, bu in his case odd harmonic cosine erms raher han sine. You may recall ha his paricular square wave was used earlier and we have already skeched he form of he Fourier series for, 3, 4 and 5 erms in Figure 8. Clearly, in finding he Fourier series of square waves, he inegraion is paricularly simple because f() akes on piecewise consan values. For oher funcions, such as saw-ooh waves his will no be he case. Before we ackle such funcions however we shall generalise our formulae for he Fourier coefficiens a n, b n o he case of a periodic funcion of arbirary period, raher han confining ourselves o period. HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 3

16 5. Fourier series for funcions of general period This is a sraighforward exension of he period case ha we have already discussed. Using x (insead of ) emporarily as he variable. We have seen ha a periodic funcion f(x) has a Fourier series f(x) = a + (a n cos nx + b n sin nx) wih a n = f(x) cos nx dx n =,,,... b n = f(x) sin nx dx n =,,... Suppose we now change he variable o where x = T. Thus x = corresponds o = T/ and x = corresponds o = T/. Hence regarded as a funcion of, we have a funcion wih period T. Making he subsiuion x =, and hence dx = a n = T b n = T T T T T T T d, in he expressions for a n and b n we obain ( ) n f() cos d T n =,,... ( ) n f() sin d T n =,... These inegrals give he Fourier coefficiens for a funcion of period T whose Fourier series is f() = a + { ( ) ( )} n n a n cos + b n sin T T Various oher noaions are commonly used in his case e.g. i is someimes convenien o wrie he period T = l. (This is paricularly useful when Fourier series arise in he soluion of parial differenial equaions.) Anoher alernaive is o use he angular frequency ω and pu T = /ω. Task Wrie down he form of he Fourier series and expressions for he coefficiens if (a) T = l (b) T = /ω. Your soluion 4 HELM (8): Workbook 3: Fourier Series

17 (a) f() = a + { ( ) ( )} n n a n cos + b n sin wih a n = l ( ) n f() cos d l l l l l and similarly for b n. (b) f() = a + {a n cos(nω) + b n sin(nω)} wih a n = ω ω f() cos(nω) d ω and similarly for b n. You should noe ha, as usual, any convenien inegraion range of lengh T (or l or ω used in evaluaing a n and b n. ) can be Example Find he Fourier series of he funcion shown in Figure which is a saw-ooh wave wih alernae porions removed. f() Figure Soluion Here he period T = l = 4 so l =. The Fourier series will have he form f() = a + { ( ) ( )} n n a n cos + b n sin The coefficiens a n are given by a n = ( ) n f() cos d where { < < f() = < < Hence a n = ( ) n cos d. f( + 4) = f() HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 5

18 Soluion (cond.) The inegraion is readily performed using inegraion by pars: ( ) n cos d = = = [ 4 n n sin [ cos ( )] n ( )] n 4 (cos n ). n Hence, since a n = cos( n )d n =, 4, 6,... a n = 4 n =, 3, 5,... n The consan erm is a where a = Similarly b n = ( ) n sin d where ( ) n sin d = [ n cos ( )] n d =. n + n The second inegral gives zero. Hence b n = n =, 4, 6,... n cos n = n + n =, 3, 5,... n ( ) n sin d n ( ) n cos d. Hence, using all hese resuls for he Fourier coefficiens, he required Fourier series is f() = 4 ( ) {cos + ( ) 3 9 cos + ( ) } 5 5 cos { ( ) sin ( ) sin + ( ) } 3 3 sin... Noice ha because he Fourier coefficiens depend on n (raher han as was he case for n he square wave) he sinusoidal componens in he Fourier series have quie rapidly decreasing ampliudes. We would herefore expec o be able o approximae he original saw-ooh funcion using only a quie small number of erms in he series. 6 HELM (8): Workbook 3: Fourier Series

19 Task Obain he Fourier series of he funcion f() = < < f( + ) = f() f() Firs wrie ou he form of he Fourier series in his case: Your soluion Since T = l = and since he funcion has a non-zero average value, he form of he Fourier series is a + {a n (cos n) + b n sin(n)} Now wrie ou inegral expressions for a n and b n. Will here be a consan erm in he Fourier series? Your soluion Because he funcion is non-negaive here will be a consan erm. Since T = l = hen l = and we have a n = b n = cos(n) d n =,,,... sin(n) d n =,,... The consan erm will be a where a = d. HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 7

20 Now evaluae he inegrals. Try o spo he value of he inegral for b n so as o avoid inegraion. Noe ha he inegrand is an even funcions for a n and an odd funcon for b n. Your soluion The inegral for b n is zero for all n because he inegrand is an odd funcion of. Since he inegrand is even in he inegrals for a n we can wrie a n = cos n d n =,,,... The consan erm will be a o where a = d = 3. For n =,, 3,... we mus inegrae by pars (wice) { [ ] a n = n sin(n) } sin(n) d n { [ = 4 ] n n cos(n) + } cos(n) d. n The inegral in he second erm gives zero so a n = 4 cos n. n Now wriing ou he final form of he Fourier series we have f() = cos n cos(n) = n { cos() + 4 cos() 9 } cos(3) HELM (8): Workbook 3: Fourier Series

21 Exercises For each of he following periodic signals skech he given funcion over a few periods find he rigonomeric Fourier coefficiens wrie ou he firs few erms of he Fourier series. < < /. f() = f( + ) = f() / < < square wave. f() = < < f( + ) = f() T/ < < 3. f() = f( + T ) = f() < < T/ < < 4. f() = f( + ) = f() < < T/ < < 5. f() = A sin T < < T/ s { cos 3 cos 3 }... f( + T ) = f() cos { sin sin 3 sin 5 sin { } cos cos 3 cos 4 cos { 4 sin ω + 3 sin 3 ω + 5 } sin 5ω +... where ω = /T. { 6 cos + A + A sin ω A square wave half-wave recifier sin 6 6 } +... } cos cos { ( 4 ) sin ( sin ) sin 3 4 } 3 3 sin { } cos ω cos 4ω + ()(3) (3)(5) +... HELM (8): Secion 3.: Represening Periodic Funcions by Fourier Series 9

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du.

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du. MATH 3B: MIDTERM REVIEW JOE HUGHES. Inegraion by Pars. Evaluae 3 e. Soluion: Firs make he subsiuion u =. Then =, hence 3 e = e = ue u Now inegrae by pars o ge ue u = ue u e u + C and subsiue he definiion

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

About the HELM Project HELM (Helping Engineers Learn Mathematics) materials were the outcome of a three-year curriculum development project

About the HELM Project HELM (Helping Engineers Learn Mathematics) materials were the outcome of a three-year curriculum development project Abou he HELM Projec HELM (Helping Engineers Learn Mahemaics) maerials were he oucome of a hree-year curriculum developmen projec underaken by a consorium of five English universiies led by Loughborough

More information

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence

MATH 4330/5330, Fourier Analysis Section 6, Proof of Fourier s Theorem for Pointwise Convergence MATH 433/533, Fourier Analysis Secion 6, Proof of Fourier s Theorem for Poinwise Convergence Firs, some commens abou inegraing periodic funcions. If g is a periodic funcion, g(x + ) g(x) for all real x,

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

6.003 Homework #8 Solutions

6.003 Homework #8 Solutions 6.003 Homework #8 Soluions Problems. Fourier Series Deermine he Fourier series coefficiens a k for x () shown below. x ()= x ( + 0) 0 a 0 = 0 a k = e /0 sin(/0) for k 0 a k = π x()e k d = 0 0 π e 0 k d

More information

ES.1803 Topic 22 Notes Jeremy Orloff

ES.1803 Topic 22 Notes Jeremy Orloff ES.83 Topic Noes Jeremy Orloff Fourier series inroducion: coninued. Goals. Be able o compue he Fourier coefficiens of even or odd periodic funcion using he simplified formulas.. Be able o wrie and graph

More information

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k Challenge Problems DIS 03 and 0 March 6, 05 Choose one of he following problems, and work on i in your group. Your goal is o convince me ha your answer is correc. Even if your answer isn compleely correc,

More information

15. Vector Valued Functions

15. Vector Valued Functions 1. Vecor Valued Funcions Up o his poin, we have presened vecors wih consan componens, for example, 1, and,,4. However, we can allow he componens of a vecor o be funcions of a common variable. For example,

More information

Echocardiography Project and Finite Fourier Series

Echocardiography Project and Finite Fourier Series Echocardiography Projec and Finie Fourier Series 1 U M An echocardiagram is a plo of how a porion of he hear moves as he funcion of ime over he one or more hearbea cycles If he hearbea repeas iself every

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier

Representing a Signal. Continuous-Time Fourier Methods. Linearity and Superposition. Real and Complex Sinusoids. Jean Baptiste Joseph Fourier Represening a Signal Coninuous-ime ourier Mehods he convoluion mehod for finding he response of a sysem o an exciaion aes advanage of he lineariy and imeinvariance of he sysem and represens he exciaion

More information

Chapter 4 The Fourier Series and Fourier Transform

Chapter 4 The Fourier Series and Fourier Transform Represenaion of Signals in Terms of Frequency Componens Chaper 4 The Fourier Series and Fourier Transform Consider he CT signal defined by x () = Acos( ω + θ ), = The frequencies `presen in he signal are

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

6.003 Homework #9 Solutions

6.003 Homework #9 Solutions 6.00 Homework #9 Soluions Problems. Fourier varieies a. Deermine he Fourier series coefficiens of he following signal, which is periodic in 0. x () 0 0 a 0 5 a k sin πk 5 sin πk 5 πk for k 0 a k 0 πk j

More information

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx.

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx. . Use Simpson s rule wih n 4 o esimae an () +. Soluion: Since we are using 4 seps, 4 Thus we have [ ( ) f() + 4f + f() + 4f 3 [ + 4 4 6 5 + + 4 4 3 + ] 5 [ + 6 6 5 + + 6 3 + ]. 5. Our funcion is f() +.

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions

MA 214 Calculus IV (Spring 2016) Section 2. Homework Assignment 1 Solutions MA 14 Calculus IV (Spring 016) Secion Homework Assignmen 1 Soluions 1 Boyce and DiPrima, p 40, Problem 10 (c) Soluion: In sandard form he given firs-order linear ODE is: An inegraing facor is given by

More information

6.003 Homework #9 Solutions

6.003 Homework #9 Solutions 6.003 Homework #9 Soluions Problems. Fourier varieies a. Deermine he Fourier series coefficiens of he following signal, which is periodic in 0. x () 0 3 0 a 0 5 a k a k 0 πk j3 e 0 e j πk 0 jπk πk e 0

More information

6.2 Transforms of Derivatives and Integrals.

6.2 Transforms of Derivatives and Integrals. SEC. 6.2 Transforms of Derivaives and Inegrals. ODEs 2 3 33 39 23. Change of scale. If l( f ()) F(s) and c is any 33 45 APPLICATION OF s-shifting posiive consan, show ha l( f (c)) F(s>c)>c (Hin: In Probs.

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Section 7.4 Modeling Changing Amplitude and Midline

Section 7.4 Modeling Changing Amplitude and Midline 488 Chaper 7 Secion 7.4 Modeling Changing Ampliude and Midline While sinusoidal funcions can model a variey of behaviors, i is ofen necessary o combine sinusoidal funcions wih linear and exponenial curves

More information

Chapter 2 : Fourier Series. Chapter 3 : Fourier Series

Chapter 2 : Fourier Series. Chapter 3 : Fourier Series Chaper 2 : Fourier Series.0 Inroducion Fourier Series : represenaion of periodic signals as weighed sums of harmonically relaed frequencies. If a signal x() is periodic signal, hen x() can be represened

More information

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3. Mah Rahman Exam Review Soluions () Consider he IVP: ( 4)y 3y + 4y = ; y(3) = 0, y (3) =. (a) Please deermine he longes inerval for which he IVP is guaraneed o have a unique soluion. Soluion: The disconinuiies

More information

Advanced Integration Techniques: Integration by Parts We may differentiate the product of two functions by using the product rule:

Advanced Integration Techniques: Integration by Parts We may differentiate the product of two functions by using the product rule: Avance Inegraion Techniques: Inegraion by Pars We may iffereniae he prouc of wo funcions by using he prouc rule: x f(x)g(x) = f (x)g(x) + f(x)g (x). Unforunaely, fining an anierivaive of a prouc is no

More information

Short Introduction to Fractional Calculus

Short Introduction to Fractional Calculus . Shor Inroducion o Fracional Calculus Mauro Bologna Deparameno de Física, Faculad de Ciencias Universidad de Tarapacá, Arica, Chile email: mbologna@ua.cl Absrac In he pas few years fracional calculus

More information

Chapter 7: Solving Trig Equations

Chapter 7: Solving Trig Equations Haberman MTH Secion I: The Trigonomeric Funcions Chaper 7: Solving Trig Equaions Le s sar by solving a couple of equaions ha involve he sine funcion EXAMPLE a: Solve he equaion sin( ) The inverse funcions

More information

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x . 1 Mah 211 Homework #3 February 2, 2001 2.4.3. y + (2/x)y = (cos x)/x 2 Answer: Compare y + (2/x) y = (cos x)/x 2 wih y = a(x)x + f(x)and noe ha a(x) = 2/x. Consequenly, an inegraing facor is found wih

More information

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004 ODEs II, Lecure : Homogeneous Linear Sysems - I Mike Raugh March 8, 4 Inroducion. In he firs lecure we discussed a sysem of linear ODEs for modeling he excreion of lead from he human body, saw how o ransform

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Week #13 - Integration by Parts & Numerical Integration Section 7.2

Week #13 - Integration by Parts & Numerical Integration Section 7.2 Week #3 - Inegraion by Pars & Numerical Inegraion Secion 7. From Calculus, Single Variable by Hughes-Halle, Gleason, McCallum e. al. Copyrigh 5 by John Wiley & Sons, Inc. This maerial is used by permission

More information

dy dx = xey (a) y(0) = 2 (b) y(1) = 2.5 SOLUTION: See next page

dy dx = xey (a) y(0) = 2 (b) y(1) = 2.5 SOLUTION: See next page Assignmen 1 MATH 2270 SOLUTION Please wrie ou complee soluions for each of he following 6 problems (one more will sill be added). You may, of course, consul wih your classmaes, he exbook or oher resources,

More information

4.6 One Dimensional Kinematics and Integration

4.6 One Dimensional Kinematics and Integration 4.6 One Dimensional Kinemaics and Inegraion When he acceleraion a( of an objec is a non-consan funcion of ime, we would like o deermine he ime dependence of he posiion funcion x( and he x -componen of

More information

The Fundamental Theorems of Calculus

The Fundamental Theorems of Calculus FunamenalTheorems.nb 1 The Funamenal Theorems of Calculus You have now been inrouce o he wo main branches of calculus: ifferenial calculus (which we inrouce wih he angen line problem) an inegral calculus

More information

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux Gues Lecures for Dr. MacFarlane s EE3350 Par Deux Michael Plane Mon., 08-30-2010 Wrie name in corner. Poin ou his is a review, so I will go faser. Remind hem o go lisen o online lecure abou geing an A

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow KEY Mah 334 Miderm III Fall 28 secions and 3 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his

More information

From Complex Fourier Series to Fourier Transforms

From Complex Fourier Series to Fourier Transforms Topic From Complex Fourier Series o Fourier Transforms. Inroducion In he previous lecure you saw ha complex Fourier Series and is coeciens were dened by as f ( = n= C ne in! where C n = T T = T = f (e

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

THE SINE INTEGRAL. x dt t

THE SINE INTEGRAL. x dt t THE SINE INTEGRAL As one learns in elemenary calculus, he limi of sin(/ as vanishes is uniy. Furhermore he funcion is even and has an infinie number of zeros locaed a ±n for n1,,3 Is plo looks like his-

More information

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow KEY Mah 334 Miderm III Winer 008 secion 00 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2.

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2. THE BERNOULLI NUMBERS The Bernoulli numbers are defined here by he exponenial generaing funcion ( e The firs one is easy o compue: (2 and (3 B 0 lim 0 e lim, 0 e ( d B lim 0 d e +e e lim 0 (e 2 lim 0 2(e

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

4.1 - Logarithms and Their Properties

4.1 - Logarithms and Their Properties Chaper 4 Logarihmic Funcions 4.1 - Logarihms and Their Properies Wha is a Logarihm? We define he common logarihm funcion, simply he log funcion, wrien log 10 x log x, as follows: If x is a posiive number,

More information

ME 452 Fourier Series and Fourier Transform

ME 452 Fourier Series and Fourier Transform ME 452 Fourier Series and Fourier ransform Fourier series From Joseph Fourier in 87 as a resul of his sudy on he flow of hea. If f() is almos any periodic funcion i can be wrien as an infinie sum of sines

More information

Math 10B: Mock Mid II. April 13, 2016

Math 10B: Mock Mid II. April 13, 2016 Name: Soluions Mah 10B: Mock Mid II April 13, 016 1. ( poins) Sae, wih jusificaion, wheher he following saemens are rue or false. (a) If a 3 3 marix A saisfies A 3 A = 0, hen i canno be inverible. True.

More information

5.1 - Logarithms and Their Properties

5.1 - Logarithms and Their Properties Chaper 5 Logarihmic Funcions 5.1 - Logarihms and Their Properies Suppose ha a populaion grows according o he formula P 10, where P is he colony size a ime, in hours. When will he populaion be 2500? We

More information

Linear Surface Gravity Waves 3., Dispersion, Group Velocity, and Energy Propagation

Linear Surface Gravity Waves 3., Dispersion, Group Velocity, and Energy Propagation Chaper 4 Linear Surface Graviy Waves 3., Dispersion, Group Velociy, and Energy Propagaion 4. Descripion In many aspecs of wave evoluion, he concep of group velociy plays a cenral role. Mos people now i

More information

EXERCISES FOR SECTION 1.5

EXERCISES FOR SECTION 1.5 1.5 Exisence and Uniqueness of Soluions 43 20. 1 v c 21. 1 v c 1 2 4 6 8 10 1 2 2 4 6 8 10 Graph of approximae soluion obained using Euler s mehod wih = 0.1. Graph of approximae soluion obained using Euler

More information

8. Basic RL and RC Circuits

8. Basic RL and RC Circuits 8. Basic L and C Circuis This chaper deals wih he soluions of he responses of L and C circuis The analysis of C and L circuis leads o a linear differenial equaion This chaper covers he following opics

More information

Lecture 2: Optics / C2: Quantum Information and Laser Science

Lecture 2: Optics / C2: Quantum Information and Laser Science Lecure : Opics / C: Quanum Informaion and Laser Science Ocober 9, 8 1 Fourier analysis This branch of analysis is exremely useful in dealing wih linear sysems (e.g. Maxwell s equaions for he mos par),

More information

Math 333 Problem Set #2 Solution 14 February 2003

Math 333 Problem Set #2 Solution 14 February 2003 Mah 333 Problem Se #2 Soluion 14 February 2003 A1. Solve he iniial value problem dy dx = x2 + e 3x ; 2y 4 y(0) = 1. Soluion: This is separable; we wrie 2y 4 dy = x 2 + e x dx and inegrae o ge The iniial

More information

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions Muli-Period Sochasic Models: Opimali of (s, S) Polic for -Convex Objecive Funcions Consider a seing similar o he N-sage newsvendor problem excep ha now here is a fixed re-ordering cos (> 0) for each (re-)order.

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Chapter 8 The Complete Response of RL and RC Circuits

Chapter 8 The Complete Response of RL and RC Circuits Chaper 8 The Complee Response of RL and RC Circuis Seoul Naional Universiy Deparmen of Elecrical and Compuer Engineering Wha is Firs Order Circuis? Circuis ha conain only one inducor or only one capacior

More information

Math 106: Review for Final Exam, Part II. (x x 0 ) 2 = !

Math 106: Review for Final Exam, Part II. (x x 0 ) 2 = ! Mah 6: Review for Final Exam, Par II. Use a second-degree Taylor polynomial o esimae 8. We choose f(x) x and x 7 because 7 is he perfec cube closes o 8. f(x) x / f(7) f (x) x / f (7) x / 7 / 7 f (x) 9

More information

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4.

Reading from Young & Freedman: For this topic, read sections 25.4 & 25.5, the introduction to chapter 26 and sections 26.1 to 26.2 & 26.4. PHY1 Elecriciy Topic 7 (Lecures 1 & 11) Elecric Circuis n his opic, we will cover: 1) Elecromoive Force (EMF) ) Series and parallel resisor combinaions 3) Kirchhoff s rules for circuis 4) Time dependence

More information

on the interval (x + 1) 0! x < ", where x represents feet from the first fence post. How many square feet of fence had to be painted?

on the interval (x + 1) 0! x < , where x represents feet from the first fence post. How many square feet of fence had to be painted? Calculus II MAT 46 Improper Inegrals A mahemaician asked a fence painer o complee he unique ask of paining one side of a fence whose face could be described by he funcion y f (x on he inerval (x + x

More information

Differential Equations

Differential Equations Mah 21 (Fall 29) Differenial Equaions Soluion #3 1. Find he paricular soluion of he following differenial equaion by variaion of parameer (a) y + y = csc (b) 2 y + y y = ln, > Soluion: (a) The corresponding

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

Mon Apr 9 EP 7.6 Convolutions and Laplace transforms. Announcements: Warm-up Exercise:

Mon Apr 9 EP 7.6 Convolutions and Laplace transforms. Announcements: Warm-up Exercise: Mah 225-4 Week 3 April 9-3 EP 7.6 - convoluions; 6.-6.2 - eigenvalues, eigenvecors and diagonalizabiliy; 7. - sysems of differenial equaions. Mon Apr 9 EP 7.6 Convoluions and Laplace ransforms. Announcemens:

More information

Predator - Prey Model Trajectories and the nonlinear conservation law

Predator - Prey Model Trajectories and the nonlinear conservation law Predaor - Prey Model Trajecories and he nonlinear conservaion law James K. Peerson Deparmen of Biological Sciences and Deparmen of Mahemaical Sciences Clemson Universiy Ocober 28, 213 Ouline Drawing Trajecories

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

Math 334 Test 1 KEY Spring 2010 Section: 001. Instructor: Scott Glasgow Dates: May 10 and 11.

Math 334 Test 1 KEY Spring 2010 Section: 001. Instructor: Scott Glasgow Dates: May 10 and 11. 1 Mah 334 Tes 1 KEY Spring 21 Secion: 1 Insrucor: Sco Glasgow Daes: Ma 1 and 11. Do NOT wrie on his problem saemen bookle, excep for our indicaion of following he honor code jus below. No credi will be

More information

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details!

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details! MAT 257, Handou 6: Ocober 7-2, 20. I. Assignmen. Finish reading Chaper 2 of Spiva, rereading earlier secions as necessary. handou and fill in some missing deails! II. Higher derivaives. Also, read his

More information

SMT 2014 Calculus Test Solutions February 15, 2014 = 3 5 = 15.

SMT 2014 Calculus Test Solutions February 15, 2014 = 3 5 = 15. SMT Calculus Tes Soluions February 5,. Le f() = and le g() =. Compue f ()g (). Answer: 5 Soluion: We noe ha f () = and g () = 6. Then f ()g () =. Plugging in = we ge f ()g () = 6 = 3 5 = 5.. There is a

More information

ENGI 9420 Engineering Analysis Assignment 2 Solutions

ENGI 9420 Engineering Analysis Assignment 2 Solutions ENGI 940 Engineering Analysis Assignmen Soluions 0 Fall [Second order ODEs, Laplace ransforms; Secions.0-.09]. Use Laplace ransforms o solve he iniial value problem [0] dy y, y( 0) 4 d + [This was Quesion

More information

The equation to any straight line can be expressed in the form:

The equation to any straight line can be expressed in the form: Sring Graphs Par 1 Answers 1 TI-Nspire Invesigaion Suden min Aims Deermine a series of equaions of sraigh lines o form a paern similar o ha formed by he cables on he Jerusalem Chords Bridge. Deermine he

More information

Traveling Waves. Chapter Introduction

Traveling Waves. Chapter Introduction Chaper 4 Traveling Waves 4.1 Inroducion To dae, we have considered oscillaions, i.e., periodic, ofen harmonic, variaions of a physical characerisic of a sysem. The sysem a one ime is indisinguishable from

More information

We just finished the Erdős-Stone Theorem, and ex(n, F ) (1 1/(χ(F ) 1)) ( n

We just finished the Erdős-Stone Theorem, and ex(n, F ) (1 1/(χ(F ) 1)) ( n Lecure 3 - Kövari-Sós-Turán Theorem Jacques Versraëe jacques@ucsd.edu We jus finished he Erdős-Sone Theorem, and ex(n, F ) ( /(χ(f ) )) ( n 2). So we have asympoics when χ(f ) 3 bu no when χ(f ) = 2 i.e.

More information

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016

Bernoulli numbers. Francesco Chiatti, Matteo Pintonello. December 5, 2016 UNIVERSITÁ DEGLI STUDI DI PADOVA, DIPARTIMENTO DI MATEMATICA TULLIO LEVI-CIVITA Bernoulli numbers Francesco Chiai, Maeo Pinonello December 5, 206 During las lessons we have proved he Las Ferma Theorem

More information

Sections 2.2 & 2.3 Limit of a Function and Limit Laws

Sections 2.2 & 2.3 Limit of a Function and Limit Laws Mah 80 www.imeodare.com Secions. &. Limi of a Funcion and Limi Laws In secion. we saw how is arise when we wan o find he angen o a curve or he velociy of an objec. Now we urn our aenion o is in general

More information

Chapters 6 & 7: Trigonometric Functions of Angles and Real Numbers. Divide both Sides by 180

Chapters 6 & 7: Trigonometric Functions of Angles and Real Numbers. Divide both Sides by 180 Algebra Chapers & : Trigonomeric Funcions of Angles and Real Numbers Chapers & : Trigonomeric Funcions of Angles and Real Numbers - Angle Measures Radians: - a uni (rad o measure he size of an angle. rad

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signals & Sysems Prof. Mark Fowler Noe Se #1 C-T Sysems: Convoluion Represenaion Reading Assignmen: Secion 2.6 of Kamen and Heck 1/11 Course Flow Diagram The arrows here show concepual flow beween

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

System of Linear Differential Equations

System of Linear Differential Equations Sysem of Linear Differenial Equaions In "Ordinary Differenial Equaions" we've learned how o solve a differenial equaion for a variable, such as: y'k5$e K2$x =0 solve DE yx = K 5 2 ek2 x C_C1 2$y''C7$y

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

Spectral Analysis. Joseph Fourier The two representations of a signal are connected via the Fourier transform. Z x(t)exp( j2πft)dt

Spectral Analysis. Joseph Fourier The two representations of a signal are connected via the Fourier transform. Z x(t)exp( j2πft)dt Specral Analysis Asignalx may be represened as a funcion of ime as x() or as a funcion of frequency X(f). This is due o relaionships developed by a French mahemaician, physicis, and Egypologis, Joseph

More information

Wall. x(t) f(t) x(t = 0) = x 0, t=0. which describes the motion of the mass in absence of any external forcing.

Wall. x(t) f(t) x(t = 0) = x 0, t=0. which describes the motion of the mass in absence of any external forcing. MECHANICS APPLICATIONS OF SECOND-ORDER ODES 7 Mechanics applicaions of second-order ODEs Second-order linear ODEs wih consan coefficiens arise in many physical applicaions. One physical sysems whose behaviour

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively:

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively: XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

= ( ) ) or a system of differential equations with continuous parametrization (T = R

= ( ) ) or a system of differential equations with continuous parametrization (T = R XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

Y 0.4Y 0.45Y Y to a proper ARMA specification.

Y 0.4Y 0.45Y Y to a proper ARMA specification. HG Jan 04 ECON 50 Exercises II - 0 Feb 04 (wih answers Exercise. Read secion 8 in lecure noes 3 (LN3 on he common facor problem in ARMA-processes. Consider he following process Y 0.4Y 0.45Y 0.5 ( where

More information

The expectation value of the field operator.

The expectation value of the field operator. The expecaion value of he field operaor. Dan Solomon Universiy of Illinois Chicago, IL dsolom@uic.edu June, 04 Absrac. Much of he mahemaical developmen of quanum field heory has been in suppor of deermining

More information

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder#

R.#W.#Erickson# Department#of#Electrical,#Computer,#and#Energy#Engineering# University#of#Colorado,#Boulder# .#W.#Erickson# Deparmen#of#Elecrical,#Compuer,#and#Energy#Engineering# Universiy#of#Colorado,#Boulder# Chaper 2 Principles of Seady-Sae Converer Analysis 2.1. Inroducion 2.2. Inducor vol-second balance,

More information

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB

EECS 2602 Winter Laboratory 3 Fourier series, Fourier transform and Bode Plots in MATLAB EECS 6 Winer 7 Laboraory 3 Fourier series, Fourier ransform and Bode Plos in MATLAB Inroducion: The objecives of his lab are o use MATLAB:. To plo periodic signals wih Fourier series represenaion. To obain

More information

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws Chaper 5: Phenomena Phenomena: The reacion (aq) + B(aq) C(aq) was sudied a wo differen emperaures (98 K and 35 K). For each emperaure he reacion was sared by puing differen concenraions of he 3 species

More information

THE WAVE EQUATION. part hand-in for week 9 b. Any dilation v(x, t) = u(λx, λt) of u(x, t) is also a solution (where λ is constant).

THE WAVE EQUATION. part hand-in for week 9 b. Any dilation v(x, t) = u(λx, λt) of u(x, t) is also a solution (where λ is constant). THE WAVE EQUATION 43. (S) Le u(x, ) be a soluion of he wave equaion u u xx = 0. Show ha Q43(a) (c) is a. Any ranslaion v(x, ) = u(x + x 0, + 0 ) of u(x, ) is also a soluion (where x 0, 0 are consans).

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 3 Signals & Sysems Prof. Mark Fowler Noe Se #2 Wha are Coninuous-Time Signals??? Reading Assignmen: Secion. of Kamen and Heck /22 Course Flow Diagram The arrows here show concepual flow beween ideas.

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

V L. DT s D T s t. Figure 1: Buck-boost converter: inductor current i(t) in the continuous conduction mode.

V L. DT s D T s t. Figure 1: Buck-boost converter: inductor current i(t) in the continuous conduction mode. ECE 445 Analysis and Design of Power Elecronic Circuis Problem Se 7 Soluions Problem PS7.1 Erickson, Problem 5.1 Soluion (a) Firs, recall he operaion of he buck-boos converer in he coninuous conducion

More information

k 1 k 2 x (1) x 2 = k 1 x 1 = k 2 k 1 +k 2 x (2) x k series x (3) k 2 x 2 = k 1 k 2 = k 1+k 2 = 1 k k 2 k series

k 1 k 2 x (1) x 2 = k 1 x 1 = k 2 k 1 +k 2 x (2) x k series x (3) k 2 x 2 = k 1 k 2 = k 1+k 2 = 1 k k 2 k series Final Review A Puzzle... Consider wo massless springs wih spring consans k 1 and k and he same equilibrium lengh. 1. If hese springs ac on a mass m in parallel, hey would be equivalen o a single spring

More information

Circuit Variables. AP 1.1 Use a product of ratios to convert two-thirds the speed of light from meters per second to miles per second: 1 ft 12 in

Circuit Variables. AP 1.1 Use a product of ratios to convert two-thirds the speed of light from meters per second to miles per second: 1 ft 12 in Circui Variables 1 Assessmen Problems AP 1.1 Use a produc of raios o conver wo-hirds he speed of ligh from meers per second o miles per second: ( ) 2 3 1 8 m 3 1 s 1 cm 1 m 1 in 2.54 cm 1 f 12 in 1 mile

More information

Morning Time: 1 hour 30 minutes Additional materials (enclosed):

Morning Time: 1 hour 30 minutes Additional materials (enclosed): ADVANCED GCE 78/0 MATHEMATICS (MEI) Differenial Equaions THURSDAY JANUARY 008 Morning Time: hour 30 minues Addiional maerials (enclosed): None Addiional maerials (required): Answer Bookle (8 pages) Graph

More information