Although complex numbers are fundamentally disconnected from our reality, they can be used to solve science and engineering problems in two ways. First, the parameters from a real world problem can be substituted into a complex form, as presented in the last chapter. The second method is much more elegant and powerful, a way of making the complex numbers mathematically equivalent to the physical problem. This approach leads to the complex Fourier transform, a more sophisticated version of the real Fourier transform. The complex Fourier transform is important in itself, but also as a stepping stone to more powerful complex techniques, such as the Laplace and z-transforms. These complex transforms are the foundation of theoretical DSP.

The Scientist and Engineer’s Guide to Digital Signal Processing, ©1997-1998 by Steven W. Smith. For more information visit the book’s website at: www.DSPguide.com