Signal Processing and Linear Systems-B.P.Lathi copy

# P lot t he resulting fourier spectra t he matlab

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Unformatted text preview: ir s amples, they m ust b e s ampled a t t he s ame r ate ( not below t he N yquist r ate o f e ither signal). Let i k (0 ::; k :::; N l - 1) a nd 9k (0 ::; k ::; N2 - 1) b e t he c orresponding discrete sequences representing these samples. Now, C(t) = f (t) a nd if we d efine three sequences as i k t hent = T f(kT), Ck = tWe can show t hat 4 this equation. Ck = l imT_o!k * 9 (t) We generally t hink o f filtering in t erms of some hardware-oriented solution (namely, building a circuit w ith R LC c omponents a nd o perational amplifiers). However, filtering also has a software-oriented solution [a c omputer a lgorithm t hat yields t he filtered o utput y (t) for a given i nput f (t) J. T his goal c an b e c onveniently accomplished by using t he D FT. I f f (t) is t he s ignal t o b e filtered, t hen Fro t he D FT o f ik, is found. T he s pectrum Fr is t hen s haped (filtered) as desired by multiplying F r by Hro where H r a re t he s amples of t he filter t ransfer f unction H (w) [Hr = H (rwo)J. Finally, we t ake t he I DFT of F rHr t o o btain t he filtered o utput Yk [Yk = T y(kT)J. T his p rocedure is d emonstrated i n t he following example. • E xample 5 .8 T he signal f (t) in Fig. 5.18a is passed through an ideal lowpass filter of transfer function H{w) depicted in Fig. 5.18b. Using DFT, find the filter output. We have already found the 32-point DFT of f (t) (see Fig. 5.16d). Next we multiply Fr by Hr. To find H r , we recall using Fo = ~ in computing the 32-point DFT of f (t). Because Fr is 32-periodic, Hr must also be 32-periodic with samples separated by Hz. This fact means t hat Hr must be repeated every 8 Hz or 1611' r ad/s (see Fig. 5.18c). The resulting 32 samples of H r over (0 ~ w ~ 1611') are as follows: i Hr = 9k = T 9(kT), a nd Ck = T c(kT), i k * 9k * 9k. Because T # 0 in practice, there will be some error in {~ 0.5 o ~ r ::; 7 9 and 25::; r ::; 31 23 r = 8 ,24 ~ r ~ We multiply Fr with Hr. The desired output signal samples Yk are found by taking the inverse DFT of F rH r . The resulting output signal is illustrated in Fig. 5.18d. Table 5.1 gives a printout of h , F r , H r , Yr , and Yk . • 352 5 Sampling 8 I (t) 1 H (ro) (a) 5.3 T he F ast Fourier Transform ( FFT) ( b) f, No. 0 I 2 3 - 0.5 0.5 -2 t- 5 7 8 9 10 \I - 40 - 32 - 24 - 16 - 10 -8 -6 -4 -2 16 r _ o 2 24 32 40 4 :I'(Hz) 4 - 8-4 ..? 8 12 \3 I' 15 16 17 18 19 20 21 (c) 10 22 j\ - 16 ..•. - 8 ..•. o F ig. 5.18 .8 16 31 Filtering f (t) through H(w). o C omputer E xample C 5.3 Solve Example 5.8 using MATLAB. The MATLAB program of Example C5.2, where we obtained the 32-point F r , should be saved as an m-file, e.g., 'c52.m'. We can import Fr in the MATLAB environment by the command 'c52'. c52; N O=32;k=0:NO-1; H =[Ones(1,8) 0 .5 z eros(1,15) 0.5 o nes(1,7)]; Y r=H.*Fr; y k= ifft ( Yr); s tem(k,yk) 0 5.3 T he F ast Fourier Transform (FFT) T he n umber of computations required in performing the D FT was dramatically reduced by a n a lgorithm developed by Tukey a nd Cooley in 1965. 5 T his al...
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## This note was uploaded on 04/14/2013 for the course ENG 350 taught by Professor Bayliss during the Spring '13 term at Northwestern.

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