The purpose of this chapter is to introduce the reader to the two following fundamental concepts:

- the
*accuracy*of the frequency measurement when the DFT is used to evaluate a signal’s DTFT. As we will see, this accuracy depends on the number of points used to calculate the DFT; - the
*spectral resolution,*which is the ability to discern two distinct frequencies contained in the same signal. It depends on the observation time and on the weighting windows applied to the signal.

To illustrate the DFT’s use in signal spectrum observation, we will begin with a simple example.

**Example 3.1 (Sampling a complex exponential)** Consider the sequence resulting from the sampling of a complex exponential *e*^{2jπF0t} at a frequency of *F*_{s} = 1/*T*_{s}. If we set *f*_{0} = *F*_{0}/*F*_{s} and assume it to be < 1/2, we get *x*(*n*) = *e*^{2jπf0n}.

- Determine the DTFT’s expression for the sequence {
*x*(*n*) = exp(2*jπf*_{0}*n*)} where*f*_{0}= 7/32 and*n*{0,...,31}. - Using this result, find the DTFT’s values at the points of frequency
*f*=*k*/32, for*k*{0,...,31}. - Using the

command, display the modulus of the DFT of {**fft***x*(*n*)}. - Now let
*f*_{0}= 0.2. Display the modulus of the DFT of {*x*(*n*)}. How do you explain the result?

- Starting off ...

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