Presentation on theme: "Symmetry and the DTFT If we know a few things about the symmetry properties of the DTFT, it can make life simpler. First, for a real-valued sequence x(n),"— Presentation transcript:
1Symmetry and the DTFTIf we know a few things about the symmetry properties of the DTFT, it can make life simpler.First, for a real-valued sequence x(n), the amplitude spectrum (magnitude of the DTFT) is an EVEN function of w.To show this first show that,
2Symmetry and the DTFTBut we’ve assumed that x(n) is a real sequence, soand the relationship is proven
3Symmetry and the DTFT The amplitude spectrum is If w is replaced by –w, th amplitude spectrum is unchanged. X(ejw) = X(e-jw), so the amplitude spectrum is an even function of w.
4Symmetry and the DTFT The phase function is For this to be an odd function of w, the imaginary part must be odd and the real part must be even. By euler’s formula,
5Symmetry and the DTFTSince cos(wn) = cos(-wn), Re(X(ejw)) is an even function of w. Likewise, since sin(wn) = -sin(-wn), Im(X(ejw)) is an even function of w. Therefore, it is shown that the phase function is an odd function of w:
6Symmetry and the DTFT Suppose x(n) has even symmetry about the origin: ThenWhich means that X(ejw) is a real-valued function
7Periodicity and the DTFT The DTFT is a periodic function of w, with period = 2pSo the frequency response function and all other DTFT’s are periodic.One period of a DTFT completely describes the function for all values of w, so it Is usually plotted only for the interval [-p, p]
8Periodicity and the DTFT If x(n) is a real-valued sequence, the amplitude spectrum is an even function of w, AND periodic. Therefore, it is completely described by the interval [0,p]. Since the phase function is an odd function, it is also completely described by the interval [0,p].Since the phase function is an odd function, it is also completely described by the interval [0,p].
9DTFT of a Sinusoid Suppose x(n) is the complex exponential, ejfn This delta function is the Dirac (continuous time) delta function, so it has the sifting property.Taking the inverse DTFT,
10DTFT of a SinusoidSo the complex exponential sequenc looks like this in the frequency domain:2p2p2p-2p-2p+f-pfp2p2p+f
12DTFT of a SinusoidSo the DTFT of a sinusoid is a pair of impulses int the frequency domain, at the positive and negative frequency of the sinusoid, then repeated every 2p radians per samplepppppp-2p-f-2p-2p+f-p-ffp2p2p+f2p-f
13The DTFT and the Fourier Transform Suppose we have a continuous time signal xa(t), and its Fourier transform:We sample xa(t) at a sampling frequency fs, creating a discrete time signal (a sequence):This sequence has a spectrum (DTFT):
14The DTFT and the Fourier Transform I will state the following relationship now, without proof. The proof comes later:In other words, whatever the continuous time spectrum is, the spectrum of the discrete time signal obtained by sampling has the same shape, but it is periodic in frequency with period = fs
15The DTFT and the Fourier Transform If the continuous time signal has this spectrumXa(f)-2fs-fsfs2fsfThen the discrete time signal (sequence) has this spectrum:X(ej2pf)-2fs-fsfs2fsf
16The DTFT and the Fourier Transform If the continuous time signal is bandlimited (has no significant spectral content above some frequency f=B),Xa(f)-2fs-fs-BBfs2fsfThen the sequence obtained by sampling the continuous time signal looks like this in the frequency domain:
17The DTFT and the Fourier Transform X(ej2pf)-2fs-fs-BBfs2fsfAs long as fs > 2B, no problem. But if fs < 2B, it looks like this:X(ej2pf)-4fs-3fs-2fs-fs-BBfs2fs3fs4fsf
18The DTFT and the Fourier Transform Note that the spectral replicas created by sampling overlapX(ej2pf)-4fs-3fs-2fs-fs-BBfs2fs3fs4fsfThis is called aliasingTo avoid aliasing, the minimum sample frequency is given by the Nyquist criterion:
19The DTFT and the Fourier Transform And the minimum sampling frequency is called the Nyquist frequency or Nyquist rate.If the Nyquist criterion is met, the original continuous time signal xa(t) can be completely recovered from the sequence x(n) by an ideal digital to analog converter.
20The DTFT and the Fourier Transform To make sure the Nyquist criterion is met, the signal should pass through an antialiasing filter before it is sampled by the analog to digital converter (ADC):xa(t)Antiasing FilterADCx(n)The antialising filter must be designed to cut off any spectral content above ½ the sampling frequency.