Acoustical Interference Phenomena
|
|
- Shannon Lambert
- 5 years ago
- Views:
Transcription
1 cousical Inerference Phenomena When wo (or more) periodic signals are linearly superposed (i.e. added ogeher), he resulan/overall waveform ha resuls depends on he ampliude, frequency and phase informaion associaed wih he individual signals. Mahemaically, his is mos easily and ransparenly described using complex noaion. Basics of/primer on Complex Variables Complex variables are used whenever phase informaion is imporan. complex funcion, Z = X+iY consiss of wo porions, a so-called real par of Z, denoed X = Re(Z) and a socalled imaginary par of Z, denoed Y = Im(Z). The number i (-). The magniude of he complex variable, Z is designaed as Z = (Z), = (ZZ*), wih Z ZZ* where Z* is he socalled complex conjugae of Z, i.e. Z* = (Z)* = (X+iY)* = XiY, wih i* = (i)* (-). Thus, Z = (ZZ*) = (X+iY)(X+iY)* = (X+iY)(XiY) = (X + ixy ixy + Y ) = (X +Y ). Thus he magniude of Z, Z is analogous o he hypoenuse, c of a righ riangle (c = a + b ) and/or he radius of a circle, r cenered a he origin (r = x + y ). Because complex variables Z = X+iY consis of wo componens, Z can be graphically depiced as a -componen vecor Z = (X,Y) lying in he so-called complex plane, as shown in he figure below. The real componen of Z, X = Re(Z) is by convenion drawn along he x, or horizonal axis (i.e. he abscissa). The imaginary componen of Z, Y = Im(Z) is by convenion drawn along he y, or verical axis (i.e. he ordinae), as shown in he figure below. Imaginary xis: Y = Im (Z) Z = (X + Y ) ½ Z = X + iy Y X Real xis: X=Re (Z) Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
2 I can be readily seen from he above diagram ha he endpoin of he complex vecor, Z = X+iY, lies a a poin on he circumference of a circle, cenered a (X,Y) = (0,0), wih radius (i.e. magniude) Z = (X + Y ) ½ and phase angle, (defined relaive o he X-axis), of an (Y / X) (or equivalenly: an (X / Y), defined relaive o he Y-axis). Insead of using Caresian coordinaes, we can alernaively and equivalenly express he complex variable, Z in polar coordinae form, Z = Z ( + isin), since X = Z and Y = Z Sin. Recall also he rigonomeric ideniy, + Sin =, which is used in obaining he magniude of Z, Z from Z iself. If we now redefine he variable such ha ( +), i can hen be seen ha Z( = Z {( + )+ isin( +)}, wih real componen X( = Re(Z() = Z ( +), and imaginary componen Y( = Im(Z() = Z Sin( +). ime = 0, hese relaions are idenical o he above. If (for simpliciy s sake) we ake he phase angle, = 0, hen Z( = Z {(+ isin(}. ime = 0, i can be seen ha he complex variable Z(=0) is purely real, Z(=0) = X(=0), i.e. lying enirely along he x-axis, Z(=0) = Z cos0 = Z. s ime, progresses, he complex variable Z( = Z {(+ isin(} roaes in a couner-clockwise manner wih (consan angular frequency, = f radians/second, where f is he frequency (in cycles/second {cps}, or Herz {=Hz}), compleing one revoluion in he complex plane every = /f = / seconds. The variable is also known as he period of oscillaion, or period of vibraion. Linear Superposiion (ddiion) of Two Periodic Signals I is illusraive o consider he siuaion of linear superposiion of wo periodic, equalampliude, idenical-frequency signals, bu in which one signal differs in phase from he oher by 90 degrees. Since he zero of ime is arbirary, we can hus chose one signal o be purely real a ime = 0, such ha Z( = and he oher signal, Z( = isin, wih purely real ampliude, and angular frequency, for each. Then, using he rigonomeric ideniy (-B) = B + SinSinB, we see ha Sin = (90 o ) = 90 o + SinSin90 o. Thus, for his example, here, he signal Z( = isin lags (i.e. is behind) he signal Z( = by 90 degrees in phase. The resulan/oal complex ampliude, Z( is he sum of he wo individual complex ampliudes, Z( = Z( + Z( = ( + isin. We can also wrie his relaion in exponenial form, since exp(i) = e i ( + isin), exp(i) = e i ( isin), and hus ½(e i + e i ) and Sin ½i(e i e i ). Then for our example, he oal complex ampliude, Z( = Z( + Z( = ( + isin = e i, wih magniude Z( = {Z(Z*(} = =. If we had insead chosen he second ampliude o be Z( = isin, hen he signal Z( would lead (i.e. be ahead of) he signal Z( = by 90 degrees in phase. Then for his siuaion, he oal complex ampliude, Z( = Z( + Z( = ( isin = e i, wih magniude Z( = (i.e. he same as before). Thus, a change in he sign of a complex quaniy, Z( Z( physically corresponds o a phase change/shif in phase/phase advance of +80 degrees (n.b. which is also mahemaically equivalen o a phase reardaion of 80 degrees). Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
3 The same mahemaical formalism can be used for adding ogeher wo arbirary (bu sill periodic) signals, Z( = (exp{i(( + ()} and Z( = (exp{i(( + ()}. The individual ampliudes, frequencies and phases may be ime-dependen. The resulan overall complex ampliude is Zo( = Z( + Z( = (exp{i(( + ()} + (exp{i(( + ()}. Because he zero of ime is (always) arbirary, we are free o choose/redefine = 0 in such a way as o roae away one of he wo phases absorbing i as an overall/absolue phase (which is physically unobservable). Since e (x+y) = e x e y, he above formula can be rewrien as: Zo( = Z( + Z( = (exp{i(}exp{i(} + (exp{i(}exp{i(}. Muliplying boh sides of his equaion by exp{i(}: Zo( exp{i( = (exp{i(} + (exp{i(}exp{i((()}. This shif in overall phase, by an amoun exp{i(}is formally equivalen o a redefiniion o he zero of ime, and also physically corresponds o a (simulaneous) roaion of boh of he (muually-perpendicular) real and imaginary axes in he complex plane by an angle, (. The physical meaning of he remaining phase afer his redefiniion of ime/shif in overall phase is a phase difference beween he second complex ampliude, Z( relaive o he firs, Z( is ( ( (. Thus, a he (newly) redefined ime * = (/( = 0 (and hen subsiuing * he resuling overall, ime-redefined ampliude is: Zo( = (exp{i(} + (exp{i(}exp{i(} or: Zo( = (exp{i(} + (exp{i(( + ()}. The so-called phasor relaion for he wo individual complex ampliudes, Z(, Z( and he resuling overall ampliude, Zo( in he complex plane is shown in he figure below. Zo(0) Z(0) (0) (0) Z(0) The magniude of he resuling overall ampliude, Zo( can be obained from Zo( = Zo(Z*o( = Z( + Z( = (Z( + Z()(Z( + Z()* = (Z( + Z()(Z*( + Z*() = Z(Z*( + Z(Z*( + Z(Z*( + Z(Z*( = Z( + Z( + Re[Z(Z*(] = ( + ( + ((Re[exp{i(((() + ()}] = ( + ( + (({((() + (} 3 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
4 The phase angle, ( of he overall/resulan ampliude, Zo( relaive o he firs ampliude, Z( can be obained from he relaion Tan{(} Im{Zo(}/Re{Zo(, hus: Tan{(}= (Sin{((() + (}/[( + ({((() + (}] Beas Phenomenon Linearly superpose (i.e. add) wo signals wih ampliudes ( and (, and which have similar/comparable frequencies, ( ~ (, wih insananeous phase of he second signal relaive o he firs of (: 0 ( ( ( ) 0 ( o 0 0 Noe ha a he ampliude level, here is nohing explicily over and/or obvious in he above mahemaical expression for he overall/oal/resulan ampliude, o( ha easily explains he phenomenon of beas associaed wih adding ogeher wo signals ha have comparable ampliudes and frequencies. However, le us consider he (insananeous) phasor relaionship beween he individual ampliudes for he wo signals, ( and ( respecively. Their relaive iniial phase difference a ime = 0 is (=0) and he resulan/oal ampliude, o(=0) is shown in he figure below, for ime, = 0: o(0) (0) (0) (0) (0) From he law of cosines, he magniude of he oal ampliude, o( a an arbirary ime, is obained from he following: Thus, o o o ( ( ) ( ( ) 0 0 For equal ampliudes, 0 = 0 = 0, zero relaive iniial phase, = 0 and consan (i.e. ime-independen frequencies, and, his expression reduces o: 4 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved. ( 0 ( ) 0 ( ) o ( ) ( 0
5 The phase of he oal ampliude, o( relaive o ha of he firs ampliude (, a an arbirary ime, is ( and is obained from he projecions of he oal ampliude phasor, o( ono he y- and x- axes of he -D phasor plane: ( ( Sin( Tan ( ( ( ( The oal ampliude, o( = ( + ( vs. ime, is shown in he figure below, for imeindependen/consan frequencies of f = 000 Hz and f = 980 Hz, equal ampliudes of uni srengh, 0 = 0 =.0 and zero relaive phase, = 0.0 Clearly, he beas phenomenon can be seen in he above waveform of oal ampliude, o( = ( + ( vs. ime,. From he above graph, i is obvious ha he bea period, bea = /fbea = sec = /0 h sec, corresponding o a bea frequency, fbea = /bea = 0 Hz, which is simply he frequency difference, fbea f f beween f = 000 Hz and f = 980 Hz. Thus, he bea period, bea = /fbea = / f f. When f = f, he bea period becomes infiniely long, and no beas are heard. 5 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
6 In erms of he phasor diagram, as ime progresses, he individual ampliudes ( and ( acually precess a (angular) raes of = f and = f radians per second respecively, compleing one revoluion in he phasor diagram, for each cycle/each period of = / = /f and = / = /f, respecively. If a ime = 0 he wo phasors are precisely in phase wih each oher (i.e. wih iniial relaive phase = 0.0), hen he resulan/oal ampliude, o( = 0) = ( = 0) + ( = 0) will be as shown in he figure below. o(=0) = (=0) + (=0) (=0) (=0) s ime progresses, if, (phasor wih angular frequency = f = *000 = 000 radians/sec and = f = *980 = 960 radians/sec in our example above) phasor, wih higher angular frequency will precess more rapidly han phasor (by he difference in angular frequencies, = ( ) = ( ) = 40 radians/second). Thus, as ime increases, phasor will lead phasor ; evenually (a ime = ½bea = 0.05 = /40 h sec in our above example) phasor will be exacly = radians, or 80 degrees behind in phase relaive o phasor. Phasor a ime = ½bea = 0.05 sec = /40 h sec will be oriened exacly as i was a ime = 0.0 (having precessed exacly N = / = f/ = f = 5.0 revoluions in his ime period), however phasor will be poining in he opposie direcion a his insan in ime (having precessed only N = / = f/ = f = 4.5 revoluions in his same ime period), and hus he oal ampliude o( = ½bea = ( = ½bea + ( = ½bea will be zero (if he magniudes of he wo individual ampliudes are precisely equal o each oher), or minimal (if he magniudes of he wo individual ampliudes are no precisely equal o each oher), as shown in he figure below. o( = ½bea = ( = ½bea + ( = ½bea = 0 ( = ½bea = ( = ½bea s ime progresses furher, phasor will coninue o lag farher and farher behind, and evenually (a ime = bea = sec = /0 h sec in our above example) phasor, having precessed hrough N = 49.0 revoluions will now be exacly = radians, or 360 degrees (or one full revoluion) behind in phase relaive o phasor (which has precessed hrough N = 50.0 full revoluions), hus, he ne/overall resul is he same as being exacly in phase wih phasor! his poin in ime, o( = bea = ( = bea + ( = bea = ( = bea = ( = bea, and he phasor diagram looks precisely like ha a ime = 0. Thus, i should (hopefully) now be clear o he reader ha he phenomenon of beas is manifesly ha of ime-dependen alernaing consrucive/desrucive inerference beween wo periodic signals of comparable frequency, a he ampliude level. This is by no means a rivial poin, as ofen he beas phenomenon is discussed in physics exbooks in he conex of inensiy, Io( = o( = ( + (. From he above discussion, he physics origin of he beas phenomenon has absoluely nohing o do wih inensiy of he overall/ resulan signal. 6 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
7 The primary reason ha he phenomenon of beas is discussed more ofen in erms of inensiy, raher han ampliude is ha he physics is perhaps easier o undersand from he inensiy perspecive a leas mahemaically, hings appear more obvious, physically: I I o o o Le us define: ) ( ) ( ) ( ( I o nd hen le us use he mahemaical ideniy: Thus: I o The le us define: We hen obain: Using he ideniy: ( 0 ( ( ) ( ) ( ) ( ) ( We hen obain he addiional relaion, which is no usually presened and/or discussed in physics exbooks: ( ( ) I o ( ( ) ( ) 0 This laer formula shows ha here are a.) DC (i.e. zero frequency) componens/consan erms associaed wih boh ampliudes, 0 and 0, b.) nd harmonic componens wih f and f, as well as c.) a componen associaed wih he sum of he wo frequencies, = f + f, and d.) a componen associaed wih he difference of he wo frequencies, f = f f. This is a remarkably similar resul o ha associaed wih he oupu response from a sysem wih a quadraic non-linear response o a pure/single-frequency sine-wave inpu! 7 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
8 Special/Limiing Case mpliude Modulaion: When 0 >> 0 and f >> f, hen he exac expression for he oal ampliude, () () () () () () () ( () ()) () o 0 0 () () () ( () ()) () 0 0 can be approximaed by he following expression(s), neglecing erms of order m (0/0) << under he radical sign, and, defining ( (( (), and noing ha for f >> f, ( (( () (: () o 0 () 0 0 () () () () ( () ()) () () 0 0 () () () () () () () () () () () However, when f >> f, he relaive phase difference ( changes by radians (essenially) for each cycle of he frequency, f. Hence we can safely se o zero his phase difference, i.e. ( = 0 because is (ime-averaged) effec in he f >> f limi is negligible. Using he Taylor series expansion for he case when <<, he expression for he oal ampliude hen becomes: () () () () () o () () () () () () () () () m 0 The raio m (0/0) << is known as he (ampliude) modulaion deph of he highfrequency carrier wave (, wih ampliude 0 >> 0 and frequency f >> f, modulaed by he low frequency wave (, wih ampliude 0 and frequency f. This is he underlying principle of M radio M sands for mpliude Modulaion 8 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
9 Legal Disclaimer and Copyrigh Noice: Legal Disclaimer: The auhor specifically disclaims legal responsibiliy for any loss of profi, or any consequenial, incidenal, and/or oher damages resuling from he mis-use of informaion conained in his documen. The auhor has made every effor possible o ensure ha he informaion conained in his documen is facually and echnically accurae and correc. Copyrigh Noice: The conens of his documen are proeced under boh Unied Saes of merica and Inernaional Copyrigh Laws. No porion of his documen may be reproduced in any manner for commercial use wihou prior wrien permission from he auhor of his documen. The auhor grans permission for he use of informaion conained in his documen for privae, non-commercial purposes only. 9 Professor Seven Errede, Deparmen of Physics, Universiy of Illinois a Urbana- Champaign, Illinois ll righs reserved.
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 informationNon-uniform circular motion *
OpenSax-CNX module: m14020 1 Non-uniform circular moion * Sunil Kumar Singh This work is produced by OpenSax-CNX and licensed under he Creaive Commons Aribuion License 2.0 Wha do we mean by non-uniform
More informationSome 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 information23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes
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
More information15. 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 information3, so θ = arccos
Mahemaics 210 Professor Alan H Sein Monday, Ocober 1, 2007 SOLUTIONS This problem se is worh 50 poins 1 Find he angle beween he vecors (2, 7, 3) and (5, 2, 4) Soluion: Le θ be he angle (2, 7, 3) (5, 2,
More informationINDEX. Transient analysis 1 Initial Conditions 1
INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera
More informationTraveling 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 informationd 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3
and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or
More informationLecture 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 informationSection 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 informationSINUSOIDAL WAVEFORMS
SINUSOIDAL WAVEFORMS The sinusoidal waveform is he only waveform whose shape is no affeced by he response characerisics of R, L, and C elemens. Enzo Paerno CIRCUIT ELEMENTS R [ Ω ] Resisance: Ω: Ohms Georg
More informationLet 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 informationWeek 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem)
Week 1 Lecure Problems, 5 Wha if somehing oscillaes wih no obvious spring? Wha is ω? (problem se problem) Sar wih Try and ge o SHM form E. Full beer can in lake, oscillaing F = m & = ge rearrange: F =
More informationPhysics 180A Fall 2008 Test points. Provide the best answer to the following questions and problems. Watch your sig figs.
Physics 180A Fall 2008 Tes 1-120 poins Name Provide he bes answer o he following quesions and problems. Wach your sig figs. 1) The number of meaningful digis in a number is called he number of. When numbers
More informationLecture 4 Kinetics of a particle Part 3: Impulse and Momentum
MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an
More information( ) = Q 0. ( ) R = R dq. ( t) = I t
ircuis onceps The addiion of a simple capacior o a circui of resisors allows wo relaed phenomena o occur The observaion ha he ime-dependence of a complex waveform is alered by he circui is referred o as
More information4.5 Constant Acceleration
4.5 Consan Acceleraion v() v() = v 0 + a a() a a() = a v 0 Area = a (a) (b) Figure 4.8 Consan acceleraion: (a) velociy, (b) acceleraion When he x -componen of he velociy is a linear funcion (Figure 4.8(a)),
More informationIn this chapter the model of free motion under gravity is extended to objects projected at an angle. When you have completed it, you should
Cambridge Universiy Press 978--36-60033-7 Cambridge Inernaional AS and A Level Mahemaics: Mechanics Coursebook Excerp More Informaion Chaper The moion of projeciles In his chaper he model of free moion
More informationEE 101 Electrical Engineering. vrect
EE Elecrical Engineering ac heory 3. Alernaing urren heory he advanage of he alernaing waveform for elecric power is ha i can be sepped up or sepped down in poenial easily for ransmission and uilisaion.
More informationRepresenting 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 informationKINEMATICS IN ONE DIMENSION
KINEMATICS IN ONE DIMENSION PREVIEW Kinemaics is he sudy of how hings move how far (disance and displacemen), how fas (speed and velociy), and how fas ha how fas changes (acceleraion). We say ha an objec
More informationContinuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.
Time-Domain Sysem Analysis Coninuous Time. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 1. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 2 Le a sysem be described by a 2 y ( ) + a 1
More information3.1.3 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 informationSolutions from Chapter 9.1 and 9.2
Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is
More informationCircuit 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 informationSimulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010
Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid
More information1. VELOCITY AND ACCELERATION
1. VELOCITY AND ACCELERATION 1.1 Kinemaics Equaions s = u + 1 a and s = v 1 a s = 1 (u + v) v = u + as 1. Displacemen-Time Graph Gradien = speed 1.3 Velociy-Time Graph Gradien = acceleraion Area under
More informationPhysics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle
Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,
More informationMath Linear Differential Equations
Mah 65 - Linear Differenial Equaions A. J. Meir Copyrigh (C) A. J. Meir. All righs reserved. This workshee is for educaional use only. No par of his publicaion may be reproduced or ransmied for profi in
More informationIE1206 Embedded Electronics
E06 Embedded Elecronics Le Le3 Le4 Le Ex Ex P-block Documenaion, Seriecom Pulse sensors,, R, P, serial and parallel K LAB Pulse sensors, Menu program Sar of programing ask Kirchhoffs laws Node analysis
More information!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)
"#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5
More informationLecture #6: Continuous-Time Signals
EEL5: Discree-Time Signals and Sysems Lecure #6: Coninuous-Time Signals Lecure #6: Coninuous-Time Signals. Inroducion In his lecure, we discussed he ollowing opics:. Mahemaical represenaion and ransormaions
More informationEchocardiography 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 informationThe 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 informationChapters 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 informationChapter 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( ) = b n ( t) n " (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2.
Andrei Tokmakoff, MIT Deparmen of Chemisry, 3/14/007-6.4 PERTURBATION THEORY Given a Hamilonian H = H 0 + V where we know he eigenkes for H 0 : H 0 n = E n n, we can calculae he evoluion of he wavefuncion
More informationChapter 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 informationChapter 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 informationCHAPTER 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 informationExplaining Total Factor Productivity. Ulrich Kohli University of Geneva December 2015
Explaining Toal Facor Produciviy Ulrich Kohli Universiy of Geneva December 2015 Needed: A Theory of Toal Facor Produciviy Edward C. Presco (1998) 2 1. Inroducion Toal Facor Produciviy (TFP) has become
More information2.7. 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 informationACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin
ACE 56 Fall 005 Lecure 4: Simple Linear Regression Model: Specificaion and Esimaion by Professor Sco H. Irwin Required Reading: Griffihs, Hill and Judge. "Simple Regression: Economic and Saisical Model
More informationNotes 04 largely plagiarized by %khc
Noes 04 largely plagiarized by %khc Convoluion Recap Some ricks: x() () =x() x() (, 0 )=x(, 0 ) R ț x() u() = x( )d x() () =ẋ() This hen ells us ha an inegraor has impulse response h() =u(), and ha a differeniaor
More informationMath 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 informationFinal 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 informationSolution: b All the terms must have the dimension of acceleration. We see that, indeed, each term has the units of acceleration
PHYS 54 Tes Pracice Soluions Spring 8 Q: [4] Knowing ha in he ne epression a is acceleraion, v is speed, is posiion and is ime, from a dimensional v poin of view, he equaion a is a) incorrec b) correc
More informationk 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 informationKinematics Vocabulary. Kinematics and One Dimensional Motion. Position. Coordinate System in One Dimension. Kinema means movement 8.
Kinemaics Vocabulary Kinemaics and One Dimensional Moion 8.1 WD1 Kinema means movemen Mahemaical descripion of moion Posiion Time Inerval Displacemen Velociy; absolue value: speed Acceleraion Averages
More informationSOLUTIONS 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 information15. Bicycle Wheel. Graph of height y (cm) above the axle against time t (s) over a 6-second interval. 15 bike wheel
15. Biccle Wheel The graph We moun a biccle wheel so ha i is free o roae in a verical plane. In fac, wha works easil is o pu an exension on one of he axles, and ge a suden o sand on one side and hold he
More informationME 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 informationName: Total Points: Multiple choice questions [120 points]
Name: Toal Poins: (Las) (Firs) Muliple choice quesions [1 poins] Answer all of he following quesions. Read each quesion carefully. Fill he correc bubble on your scanron shee. Each correc answer is worh
More informationEE 435. Lecture 35. Absolute and Relative Accuracy DAC Design. The String DAC
EE 435 Lecure 35 Absolue and Relaive Accuracy DAC Design The Sring DAC Makekup Lecures Rm 6 Sweeney 5:00 Rm 06 Coover 6:00 o 8:00 . Review from las lecure. Summary of ime and ampliude quanizaion assessmen
More informationGuest 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 informationMatlab and Python programming: how to get started
Malab and Pyhon programming: how o ge sared Equipping readers he skills o wrie programs o explore complex sysems and discover ineresing paerns from big daa is one of he main goals of his book. In his chaper,
More informationSection 3.8, Mechanical and Electrical Vibrations
Secion 3.8, Mechanical and Elecrical Vibraions Mechanical Unis in he U.S. Cusomary and Meric Sysems Disance Mass Time Force g (Earh) Uni U.S. Cusomary MKS Sysem CGS Sysem fee f slugs seconds sec pounds
More informationLinear 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 informationMath 105 Second Midterm March 16, 2017
Mah 105 Second Miderm March 16, 2017 UMID: Insrucor: Iniials: Secion: 1. Do no open his exam unil you are old o do so. 2. Do no wrie your name anywhere on his exam. 3. This exam has 9 pages including his
More informationProblem Set #1. i z. the complex propagation constant. For the characteristic impedance:
Problem Se # Problem : a) Using phasor noaion, calculae he volage and curren waves on a ransmission line by solving he wave equaion Assume ha R, L,, G are all non-zero and independen of frequency From
More information2.3 SCHRÖDINGER AND HEISENBERG REPRESENTATIONS
Andrei Tokmakoff, MIT Deparmen of Chemisry, 2/22/2007 2-17 2.3 SCHRÖDINGER AND HEISENBERG REPRESENTATIONS The mahemaical formulaion of he dynamics of a quanum sysem is no unique. So far we have described
More informationEE 435. Lecture 31. Absolute and Relative Accuracy DAC Design. The String DAC
EE 435 Lecure 3 Absolue and Relaive Accuracy DAC Design The Sring DAC . Review from las lecure. DFT Simulaion from Malab Quanizaion Noise DACs and ADCs generally quanize boh ampliude and ime If convering
More informationMorning 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 informationR.#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 information2. 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 informationThe Simple Linear Regression Model: Reporting the Results and Choosing the Functional Form
Chaper 6 The Simple Linear Regression Model: Reporing he Resuls and Choosing he Funcional Form To complee he analysis of he simple linear regression model, in his chaper we will consider how o measure
More informationk B 2 Radiofrequency pulses and hardware
1 Exra MR Problems DC Medical Imaging course April, 214 he problems below are harder, more ime-consuming, and inended for hose wih a more mahemaical background. hey are enirely opional, bu hopefully will
More informationSingle and Double Pendulum Models
Single and Double Pendulum Models Mah 596 Projec Summary Spring 2016 Jarod Har 1 Overview Differen ypes of pendulums are used o model many phenomena in various disciplines. In paricular, single and double
More information10. 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 informationModule 2 F c i k c s la l w a s o s f dif di fusi s o i n
Module Fick s laws of diffusion Fick s laws of diffusion and hin film soluion Adolf Fick (1855) proposed: d J α d d d J (mole/m s) flu (m /s) diffusion coefficien and (mole/m 3 ) concenraion of ions, aoms
More informationDIFFERENTIAL GEOMETRY HW 5
DIFFERENTIAL GEOMETRY HW 5 CLAY SHONKWILER 3. Le M be a complee Riemannian manifold wih non-posiive secional curvaure. Prove ha d exp p v w w, for all p M, all v T p M and all w T v T p M. Proof. Le γ
More informationAP Calculus BC Chapter 10 Part 1 AP Exam Problems
AP Calculus BC Chaper Par AP Eam Problems All problems are NO CALCULATOR unless oherwise indicaed Parameric Curves and Derivaives In he y plane, he graph of he parameric equaions = 5 + and y= for, is a
More informationRC, RL and RLC circuits
Name Dae Time o Complee h m Parner Course/ Secion / Grade RC, RL and RLC circuis Inroducion In his experimen we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors.
More informationThe 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 informationNumerical Dispersion
eview of Linear Numerical Sabiliy Numerical Dispersion n he previous lecure, we considered he linear numerical sabiliy of boh advecion and diffusion erms when approimaed wih several spaial and emporal
More informationRapid Termination Evaluation for Recursive Subdivision of Bezier Curves
Rapid Terminaion Evaluaion for Recursive Subdivision of Bezier Curves Thomas F. Hain School of Compuer and Informaion Sciences, Universiy of Souh Alabama, Mobile, AL, U.S.A. Absrac Bézier curve flaening
More information2001 November 15 Exam III Physics 191
1 November 15 Eam III Physics 191 Physical Consans: Earh s free-fall acceleraion = g = 9.8 m/s 2 Circle he leer of he single bes answer. quesion is worh 1 poin Each 3. Four differen objecs wih masses:
More information5.2. The Natural Logarithm. Solution
5.2 The Naural Logarihm The number e is an irraional number, similar in naure o π. Is non-erminaing, non-repeaing value is e 2.718 281 828 59. Like π, e also occurs frequenly in naural phenomena. In fac,
More informationMotion along a Straight Line
chaper 2 Moion along a Sraigh Line verage speed and average velociy (Secion 2.2) 1. Velociy versus speed Cone in he ebook: fer Eample 2. Insananeous velociy and insananeous acceleraion (Secions 2.3, 2.4)
More informationON THE BEAT PHENOMENON IN COUPLED SYSTEMS
8 h ASCE Specialy Conference on Probabilisic Mechanics and Srucural Reliabiliy PMC-38 ON THE BEAT PHENOMENON IN COUPLED SYSTEMS S. K. Yalla, Suden Member ASCE and A. Kareem, M. ASCE NaHaz Modeling Laboraory,
More informationIB Physics Kinematics Worksheet
IB Physics Kinemaics Workshee Wrie full soluions and noes for muliple choice answers. Do no use a calculaor for muliple choice answers. 1. Which of he following is a correc definiion of average acceleraion?
More informationA. Using Newton s second law in one dimension, F net. , write down the differential equation that governs the motion of the block.
Simple SIMPLE harmonic HARMONIC moion MOTION I. Differenial equaion of moion A block is conneced o a spring, one end of which is aached o a wall. (Neglec he mass of he spring, and assume he surface is
More informationWEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x
WEEK-3 Reciaion PHYS 131 Ch. 3: FOC 1, 3, 4, 6, 14. Problems 9, 37, 41 & 71 and Ch. 4: FOC 1, 3, 5, 8. Problems 3, 5 & 16. Feb 8, 018 Ch. 3: FOC 1, 3, 4, 6, 14. 1. (a) The horizonal componen of he projecile
More information2002 November 14 Exam III Physics 191
November 4 Exam III Physics 9 Physical onsans: Earh s free-fall acceleraion = g = 9.8 m/s ircle he leer of he single bes answer. quesion is worh poin Each 3. Four differen objecs wih masses: m = kg, m
More informationdy 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 informationMATH 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 informationRoller-Coaster Coordinate System
Winer 200 MECH 220: Mechanics 2 Roller-Coaser Coordinae Sysem Imagine you are riding on a roller-coaer in which he rack goes up and down, wiss and urns. Your velociy and acceleraion will change (quie abruply),
More informationCHAPTER 12 DIRECT CURRENT CIRCUITS
CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As
More informationψ ( t) = c n ( t) t n ( )ψ( ) t ku t,t 0 ψ I V kn
MIT Deparmen of Chemisry 5.74, Spring 4: Inroducory Quanum Mechanics II p. 33 Insrucor: Prof. Andrei Tokmakoff PERTURBATION THEORY Given a Hamilonian H ( ) = H + V ( ) where we know he eigenkes for H H
More informationT L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB
Elecronic Companion EC.1. Proofs of Technical Lemmas and Theorems LEMMA 1. Le C(RB) be he oal cos incurred by he RB policy. Then we have, T L E[C(RB)] 3 E[Z RB ]. (EC.1) Proof of Lemma 1. Using he marginal
More information5. Stochastic processes (1)
Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly
More informationUnit 1 Test Review Physics Basics, Movement, and Vectors Chapters 1-3
A.P. Physics B Uni 1 Tes Reiew Physics Basics, Moemen, and Vecors Chapers 1-3 * In sudying for your es, make sure o sudy his reiew shee along wih your quizzes and homework assignmens. Muliple Choice Reiew:
More informationSUPPLEMENTARY INFORMATION
SUPPLEMENTARY INFORMATION DOI: 0.038/NCLIMATE893 Temporal resoluion and DICE * Supplemenal Informaion Alex L. Maren and Sephen C. Newbold Naional Cener for Environmenal Economics, US Environmenal Proecion
More information2.4 Cuk converter example
2.4 Cuk converer example C 1 Cuk converer, wih ideal swich i 1 i v 1 2 1 2 C 2 v 2 Cuk converer: pracical realizaion using MOSFET and diode C 1 i 1 i v 1 2 Q 1 D 1 C 2 v 2 28 Analysis sraegy This converer
More informationBook Corrections for Optimal Estimation of Dynamic Systems, 2 nd Edition
Boo Correcions for Opimal Esimaion of Dynamic Sysems, nd Ediion John L. Crassidis and John L. Junins November 17, 017 Chaper 1 This documen provides correcions for he boo: Crassidis, J.L., and Junins,
More information4.6 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 informationDecimal moved after first digit = 4.6 x Decimal moves five places left SCIENTIFIC > POSITIONAL. a) g) 5.31 x b) 0.
PHYSICS 20 UNIT 1 SCIENCE MATH WORKSHEET NAME: A. Sandard Noaion Very large and very small numbers are easily wrien using scienific (or sandard) noaion, raher han decimal (or posiional) noaion. Sandard
More informationReading 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 informationChapter 2: Principles of steady-state converter analysis
Chaper 2 Principles of Seady-Sae Converer Analysis 2.1. Inroducion 2.2. Inducor vol-second balance, capacior charge balance, and he small ripple approximaion 2.3. Boos converer example 2.4. Cuk converer
More information