FinalExamSP16Soln

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Clemson University *

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301

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Electrical Engineering

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Nov 24, 2024

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Uploaded by MinisterRainGrasshopper26

!Name: __ -~------~ Final Exam ECE301 Signa1s and Systems Thursday, May 6, 2016 Cover Sheet Write your name on this page and every page to be safe. Test Duration: 120 minutes. Coverage: Comprehensive Open Book but Closed Notes. Four two-sided handwritten sheets. Calculators NOT allowed. This test contains four problems, each with multiple parts. · You have to draw your own plots. You must show all work for each problem to receive full credit. Good luck! It was great having you in class this semester! Have a great Summer!

Problem 1. Using the Z-Transform, determine the impulse response, h[n], of the LTI system defined by the Difference Equation below. There is no partial fraction expansion needed as there is only a single pole. 1 1 y[n] = -y[n - 1] + x[n] - -x[n - 4] 2 16 You must use the Z-Transform to solve this problem, i.e., use basic Z-Transform properties and a basic Z-Transform pair to ultimately determine the impulse response h[n]. ) ( i:) :: \ - 2 h I l11 ., .... ,_, i L l l ,), _j

\ } 0. t Problem 2. The rectangular pulse Xin(t) = 4{ u(t) -u(t- 3)} of duration 3 sec with amplitude 4 is input to the following integrator Xa(t) = 1t Xin(T)dT t-1 The output xa(t) is sampled every Ts= 1/4 seconds to form x[n] = xa(nTs)· The sampling rate is fs = 4 samples/sec. Show work. Clearly label and write your final answer in the space provided on the next few pages. (a) You can simply write the numbers that comprise x[n] in sequence form (indicate with an arrow where then= 0 value is) OR do a stem plot of the DT signal x[n] . . (b) The Discrete-Time (DT) signal x[n], created as described above, is input to the DT system described by the difference equation below: ::: y[n] = -x[n] + 2x[n -1] - x[n - 2] (i) Fl;~f: .dete;~i~e the impulse response h[n] for this system. (ii) Determine the output y[n] by convolving the input x[n] defined above with the impulse response h[n]. Show all work in the space provided. You can simply write the numbers that comprise y[n] in sequence form (indicate with an arrow where then= 0 value is) OR do a stem plot of the DT signal y[n]. t ·. 'Ci ( ) ~: ~),, " r ) t ) ~· ~~~ / ,_.,,, .... _ <. t:-1 \.. "'-" t ., Lt L I ) 0 l (A ~ l\ - )-u ) \ ~--~ ! I

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) 2 Show your work and plots for Problem 2 here. ..- ~'; ' I l J -I ""' ' ·~ 1 ,1 , L'" _J ' ! t_ . . '"'.,,.,,'-·~; -·~-- :· -;::c~'"-'\'"~·-~~,~~-.}~~"'"- ~1 0. ...\ ) o o () o o -0-0 r I roto-f ~1;- o 1 01-1[ ;tolo (' . (i 0 - 1J 11 r \ ~ 1 o. _ \ 0 o 0 l > o o o o o )o o> l ::> 0 ...> > ) v1L _J 1.l .) >,) >. ., ) > > ~. u

Problem 3 (a). Consider an analog signal xa(t) with maximum frequency (bandwidth) . WM= 30 rads/sec. That is, the Fourier Transform of the analog signal Xa(t) is exactly zero for lwl > 30 rads/sec. This signal is sampled at a rate Ws = 80 rads/sec., where Ws = 27r /Ts such the time betwee11~ samples is Ts = ~~ sec. This yields the discrete-time sequence { sin ( :;f n) sin ( ~n) sin ( 3 ; n) } x[n] = Xa(nTs) = T + T + T nn s nn s 7rn s where: T - 2 7r s - 80 A reconstructed signal is formed from the samples above according, to the formula below. Determine a simple, closed-form expression for the reconstructed signal xr(t). Show work. n=-oo where: Ts= 2n and h(t) = T/!_ sin(lOt) sin( 40t) 80 10 nt nt CXl Xr(t) = L x[n]h (t - nTs) Problem 3 (b). Consider the SAME analog signal xa(t) with maximum frequency (band- width) WM = 30 rads/sec. This signal is sampled at the same rate W 8 = 80 rads/sec., but is reconstructed with a different lowpass interpolating filter according to the formula below. Does this achieve perfect reconstruction, that is, does Xr(t) = xa(t)? For this part, you do not need to determine xr(t), just need to explain whether Xr(t) = xa(t) or not. n=-oo where: Ts = 27r and h(t) =Ts~ { sin(30t) + sin(50t)} 80 2 nt .nt CXl Xr(t) = L ~[n]h (t - nTs) Problem 3 (c). Consider the SAME analog signal xa(t) with maximum frequency (band- width) WM = 30 rads/sec. This signal is sampled at the same rate W 8 = 80 rads/sec., but is reconstructed with a different lowpass interpolating filter according to the formula below. Does this achieve perfect reconstruction, that is, does Xr(t) = xa(t)? For this part, you do not need to determine Xr(t), just need to explain whether Xr(t) = xa(t) or not. n=.-oo l . T _ 27r d h() _ T 1 {sin(35t) sin(45t)} w 1ere. s - - an t - 8 - + --- 80 2 nt nt CXl Xr(t) = L x[n]h (t - nTs) Show all your work for Prob. 3, parts (a)-(b)-(c) on next page.

o) I_\ I 11 ( I ~ Show your work for Prob. 3, parts (a)-(b)-(c) below. D L ~ { ~ -~ \ ,_:---1-~_;_;;; .. ~=~ 2lz: 'Si p ~ ~ ~ i I 'l----r--- --+~-~~-~+--··---~-~~- -~ o 0 ---) > s ff ~ \ (Lt ) s ·" l l_.,..J ) l """ LU I i -~- t t~ =\a s ) :: SI r 0 i L"-l ::: r i - - s l•J -- \ } 30 ( -. ~ 0 ·- -- '-'' - tFf _)

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Problem 3 (d). Consider an analog signal xa(t) with maximum frequency (bandwidth) WM = 30 rads/sec. This signal is sampled at a rate Ws = 50 rads/sec., where Ws = 2Jr /Ts such the time between samples is Ts= ;~ sec, yielding the following discrete-time sequence: { sin ( 2 ; n) sin ( 4 ; n) sin ( 6 ; n) } x[n] = Xa(nTs) = T + T + T Kn s Kn s Kn s . 2Jr where: Ts= - 50 A reconstructed signal is formed from the samples above according to the formula below. Determine a closed-: form expression for the reconstructed signal Xr ( t). Show all work. n=-oo 2Jr h(t) __ Ts sin~2t5t) where: Ts= 50 and 11 00 Xr(t) = L x[n]h (t - nTs) Problem 3 (e). Consider the SAME analog signal xa(t) with maximum frequency (band- width) WM =1Jl.O rads/sec. This signal is sampled at the same rate Ws = 50 rads/sec., where Ws = 2K/Ts and the time between samples is Ts= ;~ sec, but offset by Ts/2 from t = 0, i.e., at the points t = nTs + Ts/2. This yields the Discrete-Time x[n] signal below: { sin (2; (n + 0.5)) sin ( 4 ; (n + 0.5)) sin ( 6 ; ( n + 0.5)) } x[n] = Xa(nTs) = ( ) + ( ) + ( ) Jr n + 0.5 Ts Jr n + 0.5 Ts Jr n + 0.5 Ts 2Jr where: T = - s 50 A recoi1structed signal is formed from the samples above according to the formula below. Determine a simple, closed-form expression for the reconstructed signal xr(t). Hint: before you do a lot of work, look at the interpolating lowpass filter being used below. n=-oo 2Jr sin(25t) where: Ts= - and h(t) =Ts--- 50 Jrt 00 Xr(t) = L xE[n]h (t - (n + 0.5)Ts) Show your work for Prob. 3, parts (d)-(e) on next page.

Show all your work for Prob. 3, parts (d)-(e) on this page. ( + r \ J \ '~ " ( So -:. - z,.,.- s 10 r 2. 5 ~

Show all your work for Prob. 3, parts (d)-(e) on this page. ":\ J I_ - - ., ) ,

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Problem 4. For each part: show all work, state which Fourier Transform pairs and/or properties you are using, and clearly indicate your final answer. Pro bl em 4 (a). Determine the Fourier Transform X ( w) of the signal defined below x(t) 1+ cos( Kt), for ltl < 1 0, for ltl > 1 (1) (2) (3) You don't need to plot X(w), just determine a closed-form expression for X(w) . Note that x(t) is an even-symmetric function of time so that its Fourier Transform X(w) is purely real-valued. There should be no j = v=T anywhere in your final answer. ) r J? c 2 2 c: f / .._;' l ) s 1 n l.

Problem 4 (b). Compute the energy E = j_: x 2 (t)dt of the signal below. 4 f'.' x(t) = ~ 4 t + --oO Show all work and clearly indicate your final answer. + "":r:·- J ~ () I {\ f l [ "· _ I - 0 lv - D G \:. IJ 0 I I 0 ~ ( ~~

Problem 4 (c). You are given that the Fourier Transform of a Gaussian pulse x(t) = e -~ 2 is X(w) = V2; e -~ 2 • That is, -t2 -w2 x(t) = e-2 +------+ X(w) =a e-2- This says that, except for the scalar a= yi21f, the functional form of the Fourier Transform is the same as in the time-domain function. Is the same true for the y(t) = te -~ 2 ? That is, is the following true: -t2 ?? -w2 y(t) = t e-2 -X(w) = j3 we-2 +------+ Determine if the above is true and, if so, determine the numerical value of (3. Show all work and clearly indicate which Fourier Transform properties you are using. -t ( D·~· ~, '

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I Problem 4 ( d). Given the real-valued signal -t2 x(t) = t e-2 a complex-valued signal is formed as y(t) = x(t) + jx(t) where: x(t) = x(t) * ~ nt Determine and plot Y(w), the Fourier Transform, of y(t). Show work and sketch the magni- tude IY ( w) I· Explicitly indicate the frequency at which Y ( w) achieves its maximum value. ( I ~ { (J ~ \.. ( \. '\ ) "" -!4~-~,~4' J. s q n ( J J -J " i},;,r- - 2j 3 2 "'\ ) -> '"''''''·,.,,, ___ ---?------~---~- ----- ) I __ ;;.., d '" \\" -1~~~~~~~~~~~~~~~~~~ -4 -3 -2 -1 0 1 2 3 4 + UO

Problem 4 (f). Determine the value of the integral below, where a is a real-valued constant with a > 0. Does the answer depend on the constant a? Show all work and explain your answer. J oo 2a d _ 77 2 2 w - .. -oo w +a

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