Note that the argument inside the second square root is always positive since R L > Z 0. The series reactance can be found as

Size: px
Start display at page:

Download "Note that the argument inside the second square root is always positive since R L > Z 0. The series reactance can be found as"

Transcription

1 Ipedace Matchig Ipedace Matchig Itroductio Ipedace atchig is the process to atch the load to a trasissio lie by a atchig etwork, as depicted i Fig Recall that the reflectios are eliiated uder the atched Fig : Ipedace atchig coditio Ipedace atchig is iportat for the followig reasos: To achieve axiu power trasfer ad iiize power loss To iprove sigal-to-oise ratio To reduce aplitude ad phase errors for power distributio etworks, eg, atea arrays There are ay choices regardig atchig etwork desig, but the followig factors ust be cosidered i the selectio of the etwork: Coplexity Badwidth Ipleetatio Adjustibility Matchig with uped Eleets ( etworks) The -sectio is cosidered the siplest type of atchig etwork There are two possible cofiguratios, as depicted i Fig (a) is the etwork for Re[ ] >, while (b) is the etwork for Re[ ] < ote that i both cofiguratios, two copoets (jx, jb) are required i order to have degree of freedo, sice the load ipedace is geerally coplex Cosider Fig (a) et = R +jx, the the ipedace see lookig ito the atchig etwork followed by the load ipedace ust be equal to, ie, = jx + jb+ /( R + jx ) Rearragig ad separatig ito real ad iagiary parts yield B( XR X ) R = ; X ( BX ) = BR X Solvig the above equatios yields B X ± R / + X = R + X R R (a) (b) Fig : -sectio atchig etworks ote that the arguet iside the secod square root is always positive sice R > The series reactace ca be foud as X X = + B R BR ote also that two solutios are geerally possible Oe ust cosider the above factors i decidig which etwork to use ikewise, for the etwork i Fig (b), the atched coditio is give by = jb+ R + j( X + X ) Rearragig ad separatig ito real ad iagiary parts yield

2 Ipedace Matchig B ( X + X ) = R ; X + X = BR Solvig for X ad B gives ± ( R ) / R X = ± R ( R ) X ; B= ote that R < i this case, so the arguet of the square root is always positive Exaple Desig a -sectio atchig etwork to atch a series RC load with a ipedace = j Ω, to a Ω lie, at a frequecy of 5 MHz 9 8 sectio atchig : reflectio coefficiet plot solutio solutio Frequecy [Hz] x 8 Sigle-Stub Tuig The ipedace atchig usig -sectios discussed previously requires luped eleets that ight ot be available, thus it is ot practical i soe cases The sigle-stub tuig is the atchig techique that uses a sigle ope-circuited or short-circuited legth of trasissio-lie (a stub ), coected either i parallel or i series with the trasissio feed lie at a certai distace fro the load ote that there are two desig paraeters, aely the legth of the stub ad the distace fro the load, which cotribute degree of freedo, as i the atchig with -sectios The choice of ope-circuited stub or short-circuited stub depeds o the type of trasissio lie edia For icrostrip lies, ope stubs are preferred due to ease of fabricatio, while for coaxial lies

3 Ipedace Matchig or waveguides, short stubs are ore desirable sice such ope-circuited stubs ted to radiate, resultig i reactace chages Shut Stubs The sigle-stub shut tuig circuit cofiguratio is show i Fig Refer to the figure, to atch the ipedace, it is required that Y = Yi = Y + Y stub Sice Y stub is purely susceptace (ie, zero coductace), the real part of Y ust be equal to Furtherore, the susceptace of Y ust cacel out the susceptace of Y stub, resultig i Y i becoes Y Usig the Sith chart akes the desig process easier The first step is to fid the distace such that the oralized adittace is o the +jb circle The fid the Fig : Sigle-stub shut tuig legth such that the stub has susceptace jb Exaple For a load ipedace = 6 j8 Ω, desig two sigle-stub (short circuit) shut tuig etworks to atch this load to a 5 Ω lie Assuig that the load is atched at GHz ad the load cosists of a resistor ad a capacitor i series solutio # solutio # 5 4 Series Stubs The sigle-stub series tuig circuit cofiguratio is show i Fig 4 Refer to the figure, to atch the ipedace, it is required that = i = + stub Sice stub is purely reactace (ie, zero resistace), the real part of ust be equal to Furtherore, the reactace of ust cacel out the reactace of stub, resultig i i becoes As i the shut tuig circuit desig, usig the Sith chart akes the desig process easier The first step is to fid the distace such Frequecy [GHz] Fig 4: Sigle-stub series tuig

4 Ipedace Matchig that the oralized ipedace is o the +jx circle The fid the legth such that the stub has reactace jx Exaple For a load ipedace = + j8 Ω, desig two sigle-stub (ope circuit) series tuig etworks to atch this load to a 5 Ω lie Assuig that the load is atched at GHz ad the load cosists of a resistor ad a iductor i series solutio # solutio # 4 Double-Stub Tuig The sigle-stub tuer requires a variable legth of lie betwee the load ad the stub, thus it is difficult to ake it adjustable The double-stub tuig show i Fig 5 uses adjustable shut stubs i fixed positios However, the double-stub tuer caot atch all load ipedaces d Y Y jb jb Y Y Y jb jb Y d Y Frequecy [GHz] Ope or shorted stub l Ope or shorted stub l Ope or shorted stub l Ope or shorted stub l (a) (b) Fig 5: Double-stub tuig (a) Origial circuit with the load a arbitrary distace fro the first stub (b) Equivalet circuit with the load trasfored to the first stub The Sith chart solutio ca be illustrated i Fig 6 First, locate y ad draw the rotated +jb circle with respect to the stub spacig d The ove the load adittace oto the rotated +jb circle (poits y, y ) usig the susceptace b, b of the stub ext, ove the poits y, y oto the +jb circle (poits y, y ) Fially, add the susceptace b, b to atch the load ipedace ote that there are two possible solutios as i the case of sigle-stub tuig 4

5 Ipedace Matchig otice that if y is iside the shaded regio i the figure, specified by g +jb circle, it is ipossible to ove this adittace oto the rotated circle, which eas that it caot be atched by a double-stub tuer (ie, there is o solutio) Therefore, this shaded regio fors a forbidde rage of load adittaces that caot be atched by this double-stub tuer Reducig the space d ca lead to the reductio i the size of this forbidde rage, however, d ust be kept sufficietly large for fabricatig two separate stubs I additio, spacigs ear or λ/ load to atchig etworks that are very frequecy sesitive I practice, stub spacigs are usually chose as λ/8 or λ/8 Furtherore, if the legth of lie betwee the load ad the first stub ca be adjusted, the y ca always be oved out of the forbidde regio Fig 6: Sith chart diagra for the operatio of a doublestub tuer Exaple 4 For a load ipedace = 6 - j8 Ω, desig a shut double-stub tuer to atch this load to a 5 Ω lie The stubs are to be ope-circuited ad are spaced λ/8 apart Also, the load is assued to cosist of a 6Ω-resistor ad a 995pF-capacitor l=489, l=498, lp=465, lp=4 6+8i 9 8 ψ ψ Frequecy [Hz] x 9 5 Quarter-Wave Trasforer Recall that, for a quarter-wavelegth trasissio lie (l = λ/4), the iput ipedace becoes Solutio # Solutio # i = / or = i Therefore, a quarter-wavelegth trasissio lie ca be used to covert a resistive load to atch a trasissio lie by choosig the proper characteristic ipedace of the quarter-wavelegth lie This is called a quarter-wave trasforer The geeral cofiguratio of this quarter-wave trasforer is show i Fig 6, where 5

6 Ipedace Matchig R = To atch a arbitrary usig the quarterwave trasforer, oe ust soehow odify the load such that it becoes purely resistive This ay be doe by addig certai luped Fig 6 eleets, trasissio lie of certai legth, tuig circuits or stubs Exaple 5 Repeat exaple by usig the quarter-wave trasforer 6

7 Ipedace Matchig 6 The Theory of Sall Reflectios Quarter-wave trasforers provide a siple ea of ipedace atchig, but caot achieve broad badwidth To obtai ore badwidth, ultisectio trasforers ca be used Sigle-sectio Trasforer Cosider the sigle-sectio trasforer show i Fig 7, the partial reflectio ad trasissio coefficiets are give by = ; = ; = ; + + T = + = ; T = + = + + The total reflectio ca the be give i ters of a ifiite su of partial reflectios ad trasissios as follows: j θ j4θ = + T T e + T T e + = + T T j θ e = Usig the geoetric series x =, for x <, x = ca be rewritte as T T e = + jθ jθ e e j θ Usig =-, Τ =+, Τ = yields + e j θ = j θ + e Fig 7 If the discotiuities betwee the ipedaces, ad, are sall, the <<, ad jθ +e Multisectio Trasforer ow cosider the ultisectio trasforer show i Fig 8 This trasforer cosists of equallegth (coesurate) sectios of trasissio lies Partial reflectio coefficiets ca be defied at each juctio as + = ; = ; = Fig 8 We also assue that all icrease or decrease ootoically across the trasforer, ad is real This iplies that will be real ad of the sae sig The the total reflectio coefficiet ca be approxiated as 7

8 Ipedace Matchig j θ j 4θ j θ ( θ ) = + e +e + + e Furtherore, assue that the trasforer ca be ade syetric, so that =, = -, etc (ote that this does ot iply that the s are syetrical) The, jθ jθ j( ) θ j( ) θ { ( e + e ) + ( e + e ) +} jθ ( θ ) = e It follows that for eve, jθ θ ) = e cos θ + cos( ) θ + + cos( ) θ + + ( / ad for odd, θ jθ ) = e { cos θ + cos( ) θ + + cos( ) θ + + cos θ} ( ( ) /, Fro these results, oe ca otice that ay desired reflectio respose (as a fuctio of θ) ca be realized by choosig the proper s ad usig eough sectios Recall the fact that a sooth fuctio ca be approxiated by a Fourier series, if eough ters are used 7 Bioial Multisectio Matchig Trasforers The passbad respose of a bioial trasforer is optiu i the sese that, for a give uber of sectios, the respose is flat as possible ear the desig frequecy Thus, such as respose is also kow as axially flat This type of respose is desiged, for a -sectio trasforer, by settig the first - derivatives of (θ) to zero, at the ceter frequecy f Such a respose ca be obtaied if j θ ( θ ) = A (+ e ) The the agitude (θ) is jθ jθ jθ ( θ ) = A e e + e = A ote that (θ) = for θ=π/ ad that (d (θ) )/dθ = at θ=π/ for =,,, - (θ=π/ correspods to the ceter frequecy f, for which l=λ/4 ad θ = β l = π /) et f, the θ = β l =, ad θ ( = ) = A(+ ) = A =, + sice for f = all sectios are of zero electrical legth Thus, A= + ow expadig (θ) accordig to the bioial expasio yields ( θ ) = A(+ e j θ ) = A = C e jθ,where C! = Sice, ( )!! j θ j θ j 4θ j θ ( θ ) = A C e = +e +e + + e, = = AC If s are assued to be sall, the followig approxiatio ca be applied: + + x = l, sice l x Therefore, + x + l + + AC ( ) C C l = = + To calculate the badwidth, let deote the axiu value of reflectio coefficiet that ca be tolerated over the passbad The, 8

9 Ipedace Matchig = A cos θ θ = cos A, where θ < π / is the lower edge of the passbad Thus, /, ad the fractioal badwidth is give by / f ( f f) 4θ 4 = = = cos f f π π A Exaple 6 Desig a three-sectio trasforer to atch a 5 Ω load to a Ω lie, ad calculate the badwidth for = 5 8 Chebyshev Multisectio Matchig Trasforers I cotrast with the bioial atchig trasforer, the Chebyshev trasforer optiizes badwidth at the expese of passbad ripple The Chebyshev trasforer is desiged by equatig (θ) to a Chebyshev polyoial, which has the optiu characteristics eeded for this type of trasforer Chebyshev Polyoial The th order Chebyshev polyoial is a polyoial of degree, ad is deoted by T (x) The first four Chebyshev polyoials are 4 T ( x) = x; T ( x) = x ; T ( x) = 4x x; T ( x) = 8x 8x Higher-order polyoials ca be foud usig the followig recurrece forula: =4 4 T ( x) = xt ( x) T ( x) Soe iportat properties of Chebyshev polyoials are listed here: For - x, T (x) I this rage, the Chebyshev polyoials oscillate betwee ± This is the equal ripple property, ad this - regio will be apped to the passbad of the atchig trasforer For x >, T (x) > This regio will be -4 apped to the frequecy rage outside the passbad For x >, T (x) icreases faster with x as x icreases Fig 8: First four Chebyshev polyoials ow, let x = cos θ for x < The it ca be show that the Chebyshev polyoials ca be expressed as (cos θ ) = cos θ, or ore geerally as T T cos( cos x) ( x) = cosh( cosh x) for x < for x > T (x) = = = 9

10 Ipedace Matchig Sice equal ripple is desirable i the passbad, it is ecessary to ap θ to x = ad π θ to x = -, where θ ad π θ are the lower ad upper edges of the passbad This ca be accoplished by replacig cos θ i the above equatio with cos θ /cos θ : T cos θ = = T (secθ ) cos cos The sec θ cos θ for θ < θ < π θ, so T (sec θ cos θ ) over this sae rage It follows that the first four ters of the Chebyshev polyoials ca be writte as T (secθ ) = secθ ; T (secθ ) = sec θ(cos θ + ) ; T (secθ ) = sec θ ( + ) secθ ; 4 T4 (secθ ) = sec θ(cos 4θ + 4cos θ + ) 4sec θ(cos θ + ) + The above results ca be used to desig atchig trasforers with up to four sectios Desig of Chebyshev Trasforers A Chebyshev equal-ripple passbad ca be sythesized by akig (θ) proportioal to T (secθ ), where deotes the uber of sectios Thus, jθ { cos θ + cos( ) θ + + cos( ) θ + } = Ae T (secθ cos ) jθ ( θ ) = e where the last ter i the series is (/) Ν/ for eve ad (-)/ for odd The costat A ca be foud fro lettig θ = : ( θ = ) = = AT + θ (secθ ), or A = + T (secθ ) ow if the axiu allowable reflectio coefficiet agitude i the passbad is (ie, the ripple), the = A, sice the axiu value of T (secθ ) i the passbad is uity Usig the approxiatio itroduced i the previous sectio yields T (secθ ) = l + It follows that l( / ) secθ = cosh cosh cosh cosh + Oce θ is kow, the fractioal badwidth ca be calculated fro f 4θ = f π Each ca be deteried by expadig T (secθ ) ad equatig siilar ters of the for cos(- )θ The followig approxiatio ca be applied to iprove the accuracy: + + = l + + Exaple 7 Desig a three-sectio Chebyshev trasforer to atch a Ω load to a 5 Ω lie, with = 5

The Binomial Multi- Section Transformer

The Binomial Multi- Section Transformer 4/4/26 The Bioial Multisectio Matchig Trasforer /2 The Bioial Multi- Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where: ( ω ) = + e +

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/21 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-25 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

The Binomial Multi-Section Transformer

The Binomial Multi-Section Transformer 4/15/2010 The Bioial Multisectio Matchig Trasforer preset.doc 1/24 The Bioial Multi-Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where:

More information

5.6 Binomial Multi-section Matching Transformer

5.6 Binomial Multi-section Matching Transformer 4/14/2010 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-250 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.

More information

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1

(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1 ROOT LOCUS TECHNIQUE 93 should be desiged differetly to eet differet specificatios depedig o its area of applicatio. We have observed i Sectio 6.4 of Chapter 6, how the variatio of a sigle paraeter like

More information

x !1! + 1!2!

x !1! + 1!2! 4 Euler-Maclauri Suatio Forula 4. Beroulli Nuber & Beroulli Polyoial 4.. Defiitio of Beroulli Nuber Beroulli ubers B (,,3,) are defied as coefficiets of the followig equatio. x e x - B x! 4.. Expreesio

More information

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting

Statistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting Statistics ad Data Aalysis i MATLAB Kedrick Kay, kedrick.kay@wustl.edu February 28, 2014 Lecture 4: Model fittig 1. The basics - Suppose that we have a set of data ad suppose that we have selected the

More information

A PROBABILITY PROBLEM

A PROBABILITY PROBLEM A PROBABILITY PROBLEM A big superarket chai has the followig policy: For every Euros you sped per buy, you ear oe poit (suppose, e.g., that = 3; i this case, if you sped 8.45 Euros, you get two poits,

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Integrals of Functions of Several Variables

Integrals of Functions of Several Variables Itegrals of Fuctios of Several Variables We ofte resort to itegratios i order to deterie the exact value I of soe quatity which we are uable to evaluate by perforig a fiite uber of additio or ultiplicatio

More information

Bernoulli Polynomials Talks given at LSBU, October and November 2015 Tony Forbes

Bernoulli Polynomials Talks given at LSBU, October and November 2015 Tony Forbes Beroulli Polyoials Tals give at LSBU, October ad Noveber 5 Toy Forbes Beroulli Polyoials The Beroulli polyoials B (x) are defied by B (x), Thus B (x) B (x) ad B (x) x, B (x) x x + 6, B (x) dx,. () B 3

More information

Chapter 2. Asymptotic Notation

Chapter 2. Asymptotic Notation Asyptotic Notatio 3 Chapter Asyptotic Notatio Goal : To siplify the aalysis of ruig tie by gettig rid of details which ay be affected by specific ipleetatio ad hardware. [1] The Big Oh (O-Notatio) : It

More information

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data

Lecture 19. Curve fitting I. 1 Introduction. 2 Fitting a constant to measured data Lecture 9 Curve fittig I Itroductio Suppose we are preseted with eight poits of easured data (x i, y j ). As show i Fig. o the left, we could represet the uderlyig fuctio of which these data are saples

More information

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions

ECE 901 Lecture 4: Estimation of Lipschitz smooth functions ECE 9 Lecture 4: Estiatio of Lipschitz sooth fuctios R. Nowak 5/7/29 Cosider the followig settig. Let Y f (X) + W, where X is a rado variable (r.v.) o X [, ], W is a r.v. o Y R, idepedet of X ad satisfyig

More information

Complex Numbers Solutions

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

More information

Orthogonal Functions

Orthogonal Functions Royal Holloway Uiversity of odo Departet of Physics Orthogoal Fuctios Motivatio Aalogy with vectors You are probably failiar with the cocept of orthogoality fro vectors; two vectors are orthogoal whe they

More information

19.1 The dictionary problem

19.1 The dictionary problem CS125 Lecture 19 Fall 2016 19.1 The dictioary proble Cosider the followig data structural proble, usually called the dictioary proble. We have a set of ites. Each ite is a (key, value pair. Keys are i

More information

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

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

More information

Binomial transform of products

Binomial transform of products Jauary 02 207 Bioial trasfor of products Khristo N Boyadzhiev Departet of Matheatics ad Statistics Ohio Norther Uiversity Ada OH 4580 USA -boyadzhiev@ouedu Abstract Give the bioial trasfors { b } ad {

More information

FIR Filter Design: Part II

FIR Filter Design: Part II EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we cosider how we might go about desigig FIR filters with arbitrary frequecy resposes, through compositio of multiple sigle-peak

More information

Bertrand s postulate Chapter 2

Bertrand s postulate Chapter 2 Bertrad s postulate Chapter We have see that the sequece of prie ubers, 3, 5, 7,... is ifiite. To see that the size of its gaps is ot bouded, let N := 3 5 p deote the product of all prie ubers that are

More information

X. Perturbation Theory

X. Perturbation Theory X. Perturbatio Theory I perturbatio theory, oe deals with a ailtoia that is coposed Ĥ that is typically exactly solvable of two pieces: a referece part ad a perturbatio ( Ĥ ) that is assued to be sall.

More information

Perturbation Theory, Zeeman Effect, Stark Effect

Perturbation Theory, Zeeman Effect, Stark Effect Chapter 8 Perturbatio Theory, Zeea Effect, Stark Effect Ufortuately, apart fro a few siple exaples, the Schrödiger equatio is geerally ot exactly solvable ad we therefore have to rely upo approxiative

More information

Chapter 4. Fourier Series

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

More information

Optimal Estimator for a Sample Set with Response Error. Ed Stanek

Optimal Estimator for a Sample Set with Response Error. Ed Stanek Optial Estiator for a Saple Set wit Respose Error Ed Staek Itroductio We develop a optial estiator siilar to te FP estiator wit respose error tat was cosidered i c08ed63doc Te first 6 pages of tis docuet

More information

REVIEW OF CALCULUS Herman J. Bierens Pennsylvania State University (January 28, 2004) x 2., or x 1. x j. ' ' n i'1 x i well.,y 2

REVIEW OF CALCULUS Herman J. Bierens Pennsylvania State University (January 28, 2004) x 2., or x 1. x j. ' ' n i'1 x i well.,y 2 REVIEW OF CALCULUS Hera J. Bieres Pesylvaia State Uiversity (Jauary 28, 2004) 1. Suatio Let x 1,x 2,...,x e a sequece of uers. The su of these uers is usually deoted y x 1 % x 2 %...% x ' j x j, or x 1

More information

distinct distinct n k n k n! n n k k n 1 if k n, identical identical p j (k) p 0 if k > n n (k)

distinct distinct n k n k n! n n k k n 1 if k n, identical identical p j (k) p 0 if k > n n (k) THE TWELVEFOLD WAY FOLLOWING GIAN-CARLO ROTA How ay ways ca we distribute objects to recipiets? Equivaletly, we wat to euerate equivalece classes of fuctios f : X Y where X = ad Y = The fuctios are subject

More information

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1)

Summer MA Lesson 13 Section 1.6, Section 1.7 (part 1) Suer MA 1500 Lesso 1 Sectio 1.6, Sectio 1.7 (part 1) I Solvig Polyoial Equatios Liear equatio ad quadratic equatios of 1 variable are specific types of polyoial equatios. Soe polyoial equatios of a higher

More information

6.867 Machine learning, lecture 7 (Jaakkola) 1

6.867 Machine learning, lecture 7 (Jaakkola) 1 6.867 Machie learig, lecture 7 (Jaakkola) 1 Lecture topics: Kerel form of liear regressio Kerels, examples, costructio, properties Liear regressio ad kerels Cosider a slightly simpler model where we omit

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

Polynomial Functions and Their Graphs

Polynomial Functions and Their Graphs Polyomial Fuctios ad Their Graphs I this sectio we begi the study of fuctios defied by polyomial expressios. Polyomial ad ratioal fuctios are the most commo fuctios used to model data, ad are used extesively

More information

Physics 219 Summary of linear response theory

Physics 219 Summary of linear response theory 1 Physics 219 Suary of liear respose theory I. INTRODUCTION We apply a sall perturbatio of stregth f(t) which is switched o gradually ( adiabatically ) fro t =, i.e. the aplitude of the perturbatio grows

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

Uncertainty Principle of Mathematics

Uncertainty Principle of Mathematics Septeber 27 Ucertaity Priciple of Matheatics Shachter Mourici Israel, Holo ourici@walla.co.il Preface This short paper prove that atheatically, Reality is ot real. This short paper is ot about Heiseberg's

More information

Jacobi symbols. p 1. Note: The Jacobi symbol does not necessarily distinguish between quadratic residues and nonresidues. That is, we could have ( a

Jacobi symbols. p 1. Note: The Jacobi symbol does not necessarily distinguish between quadratic residues and nonresidues. That is, we could have ( a Jacobi sybols efiitio Let be a odd positive iteger If 1, the Jacobi sybol : Z C is the costat fuctio 1 1 If > 1, it has a decopositio ( as ) a product of (ot ecessarily distict) pries p 1 p r The Jacobi

More information

6.4 Binomial Coefficients

6.4 Binomial Coefficients 64 Bioial Coefficiets Pascal s Forula Pascal s forula, aed after the seveteeth-cetury Frech atheaticia ad philosopher Blaise Pascal, is oe of the ost faous ad useful i cobiatorics (which is the foral ter

More information

Data Analysis and Statistical Methods Statistics 651

Data Analysis and Statistical Methods Statistics 651 Data Aalysis ad Statistical Methods Statistics 651 http://www.stat.tau.edu/~suhasii/teachig.htl Suhasii Subba Rao Exaple The itroge cotet of three differet clover plats is give below. 3DOK1 3DOK5 3DOK7

More information

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20 ECE 6341 Sprig 016 Prof. David R. Jackso ECE Dept. Notes 0 1 Spherical Wave Fuctios Cosider solvig ψ + k ψ = 0 i spherical coordiates z φ θ r y x Spherical Wave Fuctios (cot.) I spherical coordiates we

More information

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces

Lecture 10: Bounded Linear Operators and Orthogonality in Hilbert Spaces Lecture : Bouded Liear Operators ad Orthogoality i Hilbert Spaces 34 Bouded Liear Operator Let ( X, ), ( Y, ) i i be ored liear vector spaces ad { } X Y The, T is said to be bouded if a real uber c such

More information

Wavelet Transform Theory. Prof. Mark Fowler Department of Electrical Engineering State University of New York at Binghamton

Wavelet Transform Theory. Prof. Mark Fowler Department of Electrical Engineering State University of New York at Binghamton Wavelet Trasfor Theory Prof. Mark Fowler Departet of Electrical Egieerig State Uiversity of New York at Bighato What is a Wavelet Trasfor? Decopositio of a sigal ito costituet parts Note that there are

More information

REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS

REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS Nice, Côte d Azur, Frace, 27-29 Septeber 2006 REDUCING THE POSSIBILITY OF SUBJECTIVE ERROR IN THE DETERMINATION OF THE STRUCTURE-FUNCTION-BASED EFFECTIVE THERMAL CONDUCTIVITY OF BOARDS Erő Kollár, Vladiír

More information

Frequency Response of FIR Filters

Frequency Response of FIR Filters EEL335: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we itroduce the idea of the frequecy respose of LTI systems, ad focus specifically o the frequecy respose of FIR filters.. Steady-state

More information

Chapter 7 z-transform

Chapter 7 z-transform Chapter 7 -Trasform Itroductio Trasform Uilateral Trasform Properties Uilateral Trasform Iversio of Uilateral Trasform Determiig the Frequecy Respose from Poles ad Zeros Itroductio Role i Discrete-Time

More information

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions

Name Period ALGEBRA II Chapter 1B and 2A Notes Solving Inequalities and Absolute Value / Numbers and Functions Nae Period ALGEBRA II Chapter B ad A Notes Solvig Iequalities ad Absolute Value / Nubers ad Fuctios SECTION.6 Itroductio to Solvig Equatios Objectives: Write ad solve a liear equatio i oe variable. Solve

More information

Lecture Outline. 2 Separating Hyperplanes. 3 Banach Mazur Distance An Algorithmist s Toolkit October 22, 2009

Lecture Outline. 2 Separating Hyperplanes. 3 Banach Mazur Distance An Algorithmist s Toolkit October 22, 2009 18.409 A Algorithist s Toolkit October, 009 Lecture 1 Lecturer: Joatha Keler Scribes: Alex Levi (009) 1 Outlie Today we ll go over soe of the details fro last class ad ake precise ay details that were

More information

MAXIMALLY FLAT FIR FILTERS

MAXIMALLY FLAT FIR FILTERS MAXIMALLY FLAT FIR FILTERS This sectio describes a family of maximally flat symmetric FIR filters first itroduced by Herrma [2]. The desig of these filters is particularly simple due to the availability

More information

Problem. Consider the sequence a j for j N defined by the recurrence a j+1 = 2a j + j for j > 0

Problem. Consider the sequence a j for j N defined by the recurrence a j+1 = 2a j + j for j > 0 GENERATING FUNCTIONS Give a ifiite sequece a 0,a,a,, its ordiary geeratig fuctio is A : a Geeratig fuctios are ofte useful for fidig a closed forula for the eleets of a sequece, fidig a recurrece forula,

More information

Ma/CS 6a Class 22: Power Series

Ma/CS 6a Class 22: Power Series Ma/CS 6a Class 22: Power Series By Ada Sheffer Power Series Mooial: ax i. Polyoial: a 0 + a 1 x + a 2 x 2 + + a x. Power series: A x = a 0 + a 1 x + a 2 x 2 + Also called foral power series, because we

More information

42 Dependence and Bases

42 Dependence and Bases 42 Depedece ad Bases The spa s(a) of a subset A i vector space V is a subspace of V. This spa ay be the whole vector space V (we say the A spas V). I this paragraph we study subsets A of V which spa V

More information

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT TR/46 OCTOBER 974 THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION by A. TALBOT .. Itroductio. A problem i approximatio theory o which I have recetly worked [] required for its solutio a proof that the

More information

Problem Cosider the curve give parametrically as x = si t ad y = + cos t for» t» ß: (a) Describe the path this traverses: Where does it start (whe t =

Problem Cosider the curve give parametrically as x = si t ad y = + cos t for» t» ß: (a) Describe the path this traverses: Where does it start (whe t = Mathematics Summer Wilso Fial Exam August 8, ANSWERS Problem 1 (a) Fid the solutio to y +x y = e x x that satisfies y() = 5 : This is already i the form we used for a first order liear differetial equatio,

More information

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii

) is a square matrix with the property that for any m n matrix A, the product AI equals A. The identity matrix has a ii square atrix is oe that has the sae uber of rows as colus; that is, a atrix. he idetity atrix (deoted by I, I, or [] I ) is a square atrix with the property that for ay atrix, the product I equals. he

More information

Engineering Mechanics Dynamics & Vibrations. Engineering Mechanics Dynamics & Vibrations Plane Motion of a Rigid Body: Equations of Motion

Engineering Mechanics Dynamics & Vibrations. Engineering Mechanics Dynamics & Vibrations Plane Motion of a Rigid Body: Equations of Motion 1/5/013 Egieerig Mechaics Dyaics ad Vibratios Egieerig Mechaics Dyaics & Vibratios Egieerig Mechaics Dyaics & Vibratios Plae Motio of a Rigid Body: Equatios of Motio Motio of a rigid body i plae otio is

More information

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io Chapter 9 - CD compaio CHAPTER NINE CD-9.2 CD-9.2. Stages With Voltage ad Curret Gai A Geeric Implemetatio; The Commo-Merge Amplifier The advaced method preseted i the text for approximatig cutoff frequecies

More information

Ma 530 Introduction to Power Series

Ma 530 Introduction to Power Series Ma 530 Itroductio to Power Series Please ote that there is material o power series at Visual Calculus. Some of this material was used as part of the presetatio of the topics that follow. What is a Power

More information

THE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS

THE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS So far i the tudie of cotrol yte the role of the characteritic equatio polyoial i deteriig the behavior of the yte ha bee highlighted. The root of that polyoial are the pole of the cotrol yte, ad their

More information

Math 4707 Spring 2018 (Darij Grinberg): midterm 2 page 1. Math 4707 Spring 2018 (Darij Grinberg): midterm 2 with solutions [preliminary version]

Math 4707 Spring 2018 (Darij Grinberg): midterm 2 page 1. Math 4707 Spring 2018 (Darij Grinberg): midterm 2 with solutions [preliminary version] Math 4707 Sprig 08 Darij Griberg: idter page Math 4707 Sprig 08 Darij Griberg: idter with solutios [preliiary versio] Cotets 0.. Coutig first-eve tuples......................... 3 0.. Coutig legal paths

More information

5.7 Chebyshev Multi-section Matching Transformer

5.7 Chebyshev Multi-section Matching Transformer 3/8/6 5_7 Chebyshev Multisection Matching Transforers / 5.7 Chebyshev Multi-section Matching Transforer Reading Assignent: pp. 5-55 We can also build a ultisection atching network such that Γ f is a Chebyshev

More information

LC Oscillations. di Q. Kirchoff s loop rule /27/2018 1

LC Oscillations. di Q. Kirchoff s loop rule /27/2018 1 L Oscillatios Kirchoff s loop rule I di Q VL V L dt ++++ - - - - L 3/27/28 , r Q.. 2 4 6 x 6.28 I. f( x) f( x).. r.. 2 4 6 x 6.28 di dt f( x) Q Q cos( t) I Q si( t) di dt Q cos( t) 2 o x, r.. V. x f( )

More information

1 The Primal and Dual of an Optimization Problem

1 The Primal and Dual of an Optimization Problem CS 189 Itroductio to Machie Learig Fall 2017 Note 18 Previously, i our ivestigatio of SVMs, we forulated a costraied optiizatio proble that we ca solve to fid the optial paraeters for our hyperplae decisio

More information

Drift Distortions in Alice TPC Field Cage

Drift Distortions in Alice TPC Field Cage AICE / 97- Iteral Note / TPC.6.97. Drift Distortios i Alice TPC Field Cage D. Vraic Abstract Calculatios of drift distortios for the TPC field cage with two coaxial cyliders with closed eds are preseted.

More information

COMP 2804 Solutions Assignment 1

COMP 2804 Solutions Assignment 1 COMP 2804 Solutios Assiget 1 Questio 1: O the first page of your assiget, write your ae ad studet uber Solutio: Nae: Jaes Bod Studet uber: 007 Questio 2: I Tic-Tac-Toe, we are give a 3 3 grid, cosistig

More information

AVERAGE MARKS SCALING

AVERAGE MARKS SCALING TERTIARY INSTITUTIONS SERVICE CENTRE Level 1, 100 Royal Street East Perth, Wester Australia 6004 Telephoe (08) 9318 8000 Facsiile (08) 95 7050 http://wwwtisceduau/ 1 Itroductio AVERAGE MARKS SCALING I

More information

PARTIAL DIFFERENTIAL EQUATIONS SEPARATION OF VARIABLES

PARTIAL DIFFERENTIAL EQUATIONS SEPARATION OF VARIABLES Diola Bagayoko (0 PARTAL DFFERENTAL EQUATONS SEPARATON OF ARABLES. troductio As discussed i previous lectures, partial differetial equatios arise whe the depedet variale, i.e., the fuctio, varies with

More information

Fundamental Theorem of Algebra. Yvonne Lai March 2010

Fundamental Theorem of Algebra. Yvonne Lai March 2010 Fudametal Theorem of Algebra Yvoe Lai March 010 We prove the Fudametal Theorem of Algebra: Fudametal Theorem of Algebra. Let f be a o-costat polyomial with real coefficiets. The f has at least oe complex

More information

A string of not-so-obvious statements about correlation in the data. (This refers to the mechanical calculation of correlation in the data.

A string of not-so-obvious statements about correlation in the data. (This refers to the mechanical calculation of correlation in the data. STAT-UB.003 NOTES for Wedesday 0.MAY.0 We will use the file JulieApartet.tw. We ll give the regressio of Price o SqFt, show residual versus fitted plot, save residuals ad fitted. Give plot of (Resid, Price,

More information

CS 70 Second Midterm 7 April NAME (1 pt): SID (1 pt): TA (1 pt): Name of Neighbor to your left (1 pt): Name of Neighbor to your right (1 pt):

CS 70 Second Midterm 7 April NAME (1 pt): SID (1 pt): TA (1 pt): Name of Neighbor to your left (1 pt): Name of Neighbor to your right (1 pt): CS 70 Secod Midter 7 April 2011 NAME (1 pt): SID (1 pt): TA (1 pt): Nae of Neighbor to your left (1 pt): Nae of Neighbor to your right (1 pt): Istructios: This is a closed book, closed calculator, closed

More information

( ) Time-Independent Perturbation Theory. Michael Fowler 2/16/06

( ) Time-Independent Perturbation Theory. Michael Fowler 2/16/06 Tie-Idepedet Perturbatio Theory Michael Fowler /6/6 Itroductio If a ato (ot ecessarily i its groud state) is placed i a exteral electric field, the eergy levels shift, ad the wave fuctios are distorted

More information

Question 1: The magnetic case

Question 1: The magnetic case September 6, 018 Corell Uiversity, Departmet of Physics PHYS 337, Advace E&M, HW # 4, due: 9/19/018, 11:15 AM Questio 1: The magetic case I class, we skipped over some details, so here you are asked to

More information

Most text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t

Most text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t Itroductio to Differetial Equatios Defiitios ad Termiolog Differetial Equatio: A equatio cotaiig the derivatives of oe or more depedet variables, with respect to oe or more idepedet variables, is said

More information

Double Derangement Permutations

Double Derangement Permutations Ope Joural of iscrete Matheatics, 206, 6, 99-04 Published Olie April 206 i SciRes http://wwwscirporg/joural/ojd http://dxdoiorg/04236/ojd2066200 ouble erageet Perutatios Pooya aeshad, Kayar Mirzavaziri

More information

CALCULUS BASIC SUMMER REVIEW

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

More information

1 of 7 7/16/2009 6:06 AM Virtual Laboratories > 6. Radom Samples > 1 2 3 4 5 6 7 6. Order Statistics Defiitios Suppose agai that we have a basic radom experimet, ad that X is a real-valued radom variable

More information

THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION

THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION MATHEMATICA MONTISNIGRI Vol XXVIII (013) 17-5 THE GREATEST ORDER OF THE DIVISOR FUNCTION WITH INCREASING DIMENSION GLEB V. FEDOROV * * Mechaics ad Matheatics Faculty Moscow State Uiversity Moscow, Russia

More information

Chapter 15: Fourier Series

Chapter 15: Fourier Series Chapter 5: Fourier Series Ex. 5.3- Ex. 5.3- Ex. 5.- f(t) K is a Fourier Series. he coefficiets are a K; a b for. f(t) AcosZ t is a Fourier Series. a A ad all other coefficiets are zero. Set origi at t,

More information

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

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

More information

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

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

More information

SNAP Centre Workshop. Basic Algebraic Manipulation

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

More information

8.3 Perturbation theory

8.3 Perturbation theory 8.3 Perturbatio theory Slides: Video 8.3.1 Costructig erturbatio theory Text referece: Quatu Mechaics for Scietists ad gieers Sectio 6.3 (u to First order erturbatio theory ) Perturbatio theory Costructig

More information

Statistical Pattern Recognition

Statistical Pattern Recognition Statistical Patter Recogitio Classificatio: No-Parametric Modelig Hamid R. Rabiee Jafar Muhammadi Sprig 2014 http://ce.sharif.edu/courses/92-93/2/ce725-2/ Ageda Parametric Modelig No-Parametric Modelig

More information

EE Midterm Test 1 - Solutions

EE Midterm Test 1 - Solutions EE35 - Midterm Test - Solutios Total Poits: 5+ 6 Bous Poits Time: hour. ( poits) Cosider the parallel itercoectio of the two causal systems, System ad System 2, show below. System x[] + y[] System 2 The

More information

Queueing Theory II. Summary. M/M/1 Output process Networks of Queue Method of Stages. General Distributions

Queueing Theory II. Summary. M/M/1 Output process Networks of Queue Method of Stages. General Distributions Queueig Theory II Suary M/M/1 Output process Networks of Queue Method of Stages Erlag Distributio Hyperexpoetial Distributio Geeral Distributios Ebedded Markov Chais 1 M/M/1 Output Process Burke s Theore:

More information

Data Movement in Flash Memories

Data Movement in Flash Memories Data Moveet i Flash Meories Axiao (Adrew) Jiag Coputer Sciece Departet Texas A&M Uiversity College Statio, TX 77843 ajiag@cse.tau.edu Michael Lagberg Coputer Sciece Divisio Ope Uiversity of Israel Raaaa

More information

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement

Practical Spectral Anaysis (continue) (from Boaz Porat s book) Frequency Measurement Practical Spectral Aaysis (cotiue) (from Boaz Porat s book) Frequecy Measuremet Oe of the most importat applicatios of the DFT is the measuremet of frequecies of periodic sigals (eg., siusoidal sigals),

More information

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers,

We have also learned that, thanks to the Central Limit Theorem and the Law of Large Numbers, Cofidece Itervals III What we kow so far: We have see how to set cofidece itervals for the ea, or expected value, of a oral probability distributio, both whe the variace is kow (usig the stadard oral,

More information

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

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

More information

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

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

More information

Bertrand s Postulate

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

More information

Chapter 9 Computation of the Discrete. Fourier Transform

Chapter 9 Computation of the Discrete. Fourier Transform Chapter 9 Coputatio of the Discrete Fourier Trasfor Itroductio Efficiet Coputatio of the Discrete Fourier Trasfor Goertzel Algorith Deciatio-I-Tie FFT Algoriths Deciatio-I-Frequecy FFT Algoriths Ipleetatio

More information

Probabilistic Analysis of Rectilinear Steiner Trees

Probabilistic Analysis of Rectilinear Steiner Trees Probabilistic Aalysis of Rectiliear Steier Trees Chuhog Che Departet of Electrical ad Coputer Egieerig Uiversity of Widsor, Otario, Caada, N9B 3P4 E-ail: cche@uwidsor.ca Abstract Steier tree is a fudaetal

More information

A NEW DESIGN METHOD FOR IIR DIAMOND-SHAPED FILTERS

A NEW DESIGN METHOD FOR IIR DIAMOND-SHAPED FILTERS 8th Europea Sigal Processig Coferece (EUSIPCO- Aalborg, Deark, August 3-7, A EW DESIG MEHOD FOR IIR DIAMOD-SHAPED FILERS Radu Matei Faculty of Electroics, elecouicatios ad Iforatio echology, echical Uiversity

More information

9.5 Young s Double-Slit Experiment

9.5 Young s Double-Slit Experiment 9.5 Youg s Double-Slit Experiet Physics Tool box Early attepts to deostrate the iterferece of light were usuccessful because the two sources were too far apart ad out of phase, ad the wavelegth of light

More information

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

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

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course

EE / EEE SAMPLE STUDY MATERIAL. GATE, IES & PSUs Signal System. Electrical Engineering. Postal Correspondence Course Sigal-EE Postal Correspodece Course 1 SAMPLE STUDY MATERIAL Electrical Egieerig EE / EEE Postal Correspodece Course GATE, IES & PSUs Sigal System Sigal-EE Postal Correspodece Course CONTENTS 1. SIGNAL

More information

Introduction to Signals and Systems, Part V: Lecture Summary

Introduction to Signals and Systems, Part V: Lecture Summary EEL33: Discrete-Time Sigals ad Systems Itroductio to Sigals ad Systems, Part V: Lecture Summary Itroductio to Sigals ad Systems, Part V: Lecture Summary So far we have oly looked at examples of o-recursive

More information

Quadratic Functions. Before we start looking at polynomials, we should know some common terminology.

Quadratic Functions. Before we start looking at polynomials, we should know some common terminology. Quadratic Fuctios I this sectio we begi the study of fuctios defied by polyomial expressios. Polyomial ad ratioal fuctios are the most commo fuctios used to model data, ad are used extesively i mathematical

More information

Random Models. Tusheng Zhang. February 14, 2013

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

More information

Contents Two Sample t Tests Two Sample t Tests

Contents Two Sample t Tests Two Sample t Tests Cotets 3.5.3 Two Saple t Tests................................... 3.5.3 Two Saple t Tests Setup: Two Saples We ow focus o a sceario where we have two idepedet saples fro possibly differet populatios. Our

More information

COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION

COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION Fluid Dyaics ad Acoustics Office COMPARISON OF LOW WAVENUMBER MODELS FOR TURBULENT BOUNDARY LAYER EXCITATION Peter D. Lysa, Willia K. Boess, ad Joh B. Fahlie Alied Research Laboratory, Pe State Uiversity

More information