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

# W e s hall a nswer t his q uestion i n t he n ext e

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Unformatted text preview: r transform o f t he s tep function. Note t hat u (t) i s n ot a &quot; true&quot; d c signal because i t is n ot c onstant over t he i nterval - 00 t o 0 0. To synthesize a &quot; true&quot; d c, we r equire only one everlasting exponential w ith w = 0 (impulse a t w = 0). T he s ignal u (t) h as a j ump d iscontinuity a t t = O. I t is impossible to synthesize such a signal w ith a single everlasting exponential ejw ,. To synthesize this signal from everlasting exponentials, we need, in addition t o a n i mpulse a t w = 0, all frequency components, a s i ndicated b y t he t erm l /jw i n Eq. (4.29). • 0 Observe t hat t he u pper limit of e - jw' as t - &gt; 0 0 yields a n i ndeterminate answer. So we a pproach this problem by considering u (t) as a decaying exponential e -a'u(t) in t he limit as a - &gt; 0 (Fig. 4.14a). Thus u (t) Fig. 4 .14 6. 00 = -:-~ e - jw ' 1 0 t- (4.27) T he s pectrum o f cos wot consists of two impulses a t Wo a nd - wo, as shown in Fig. 4.13. T he result also follows from qualitative reasoning. An everlasting sinusoid cos wot can be synthesized by two everlasting exponentials, e jwo ' a nd e - jwo '. Therefore t he Fourier s pectrum c onsists of only two components o f frequencies Wo a nd -woo • U(w) 01_ . .......... . ........... Adding Eqs. (4.26a) and (4.26b), and using t he above formula, we o btain (4.29) tThe second term on the right-hand side of Eq. (4.28b), being an odd function of w, has zero area regardless of the value of a. As a - + 0, the second term approaches 1 / j w. 4.3 Some properties of the Fourier Transform W e n ow s tudy s ome o f t he i mportant p roperties o f t he F ourier t ransform a nd t heir i mplications a s w ell a s a pplications. B efore e mbarking o n t his s tudy, w e s hall e xplain a n i mportant a nd p ervasive a spect o f t he F ourier t ransform: t he t imefrequency d uality. 4 Continuous-Time Signal Analysis: T he Fourier Transform 252 4.3 Some P roperties of t he Fourier Transform 253 T able 4 .1 A S hort T able o f F ourier T ransforms F(w) j (t) ! (t) a&gt; 0 a + jw 1 a - jw F(ro ) a&gt; 0 J ~ 2a a2 +w 2 1 (a a&gt;O + j w)2 n! (a 6 4.3-1 E quations (4.8) show a n i nteresting fact: t he d irect a nd t he inverse transform operations are remarkably similar. These operations, required to go from j (t) t o F(w) a nd t hen from F(w) t o j (t), a re depicted graphically in Fig. 4.16. T here a re only two minor differences in these operations: t he factor 27r a ppears only in t he inverse operator, a nd t he e xponential indices in t he two operations have opposite signs. Otherwise t he two operations are symmetrical. t T his observation has farreaching consequences in t he s tudy of t he Fourier transform. I t is t he basis of t he so-called duality of time a nd frequency. T he duality principle m ay be compared with a photograph a nd i ts negative. A photograph can be obtained from i ts negative, a nd by using a n i dentical procedure, t he negative can be obtained from the phot...
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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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