CH12 - CHAPTER 12 The Fast Fourier Transform There are...

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225 CHAPTER 12 The Fast Fourier Transform There are several ways to calculate the Discrete Fourier Transform (DFT), such as solving simultaneous linear equations or the correlation method described in Chapter 8. The Fast Fourier Transform (FFT) is another method for calculating the DFT. While it produces the same result as the other approaches, it is incredibly more efficient, often reducing the computation time by hundreds . This is the same improvement as flying in a jet aircraft versus walking! If the FFT were not available, many of the techniques described in this book would not be practical. While the FFT only requires a few dozen lines of code, it is one of the most complicated algorithms in DSP. But don't despair! You can easily use published FFT routines without fully understanding the internal workings. Real DFT Using the Complex DFT J.W. Cooley and J.W. Tukey are given credit for bringing the FFT to the world in their paper: "An algorithm for the machine calculation of complex Fourier Series," Mathematics Computation , Vol. 19, 1965, pp 297-301. In retrospect, others had discovered the technique many years before. For instance, the great German mathematician Karl Friedrich Gauss (1777-1855) had used the method more than a century earlier. This early work was largely forgotten because it lacked the tool to make it practical: the digital computer . Cooley and Tukey are honored because they discovered the FFT at the right time, the beginning of the computer revolution. The FFT is based on the complex DFT , a more sophisticated version of the real DFT discussed in the last four chapters. These transforms are named for the way each represents data, that is, using complex numbers or using real numbers. The term complex does not mean that this representation is difficult or complicated, but that a specific type of mathematics is used. Complex mathematics often is difficult and complicated, but that isn't where the name comes from. Chapter 29 discusses the complex DFT and provides the background needed to understand the details of the FFT algorithm. The
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The Scientist and Engineer's Guide to Digital Signal Processing 226 FIGURE 12-1 Comparing the real and complex DFTs. The real DFT takes an N point time domain signal and creates two point frequency domain signals. The complex DFT takes two N point time N /2 % 1 domain signals and creates two N point frequency domain signals. The crosshatched regions shows the values common to the two transforms. Real DFT Complex DFT Time Domain Time Domain Frequency Domain Frequency Domain 0 N -1 0 N -1 0 N -1 0 N /2 0 N /2 0 0 N -1 N -1 N /2 N /2 Real Part Imaginary Part Real Part Imaginary Part Real Part Imaginary Part Time Domain Signal topic of this chapter is simpler: how to use the FFT to calculate the real DFT, without drowning in a mire of advanced mathematics.
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CH12 - CHAPTER 12 The Fast Fourier Transform There are...

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