Categorizing Signals (Advanced Signal Processing Toolkit)

In signal processing, you usually categorize signals into the following types:

• Stationary—For stationary signals, you assume that the spectral content of stationary signals does not change as a function of time, space, or some other independent variable. For example, you might work under the assumption that an engine vibration signal is stationary when an engine is running at a constant speed.
• Nonstationary—For nonstationary signals, you assume that the spectral content changes over time, space, or some other independent variable. For example, you might work under the assumption that an engine vibration signal is nonstationary when an engine is revving up or down.
  
  You can categorize nonstationary signals into the following types according to how the spectral content changes over time.
  • Evolutionary—The spectral contents of evolutionary signals change over time slowly. Evolutionary signals usually contain time-varying harmonics. The time-varying harmonics relate to the underlying periodic time-varying characteristic of the system that generates signals. Evolutionary signals also can contain time-varying broadband spectral contents.
  • Transient—Transient signals are the short-time events in a nonstationary signal, such as peaks, edges, breakdown points, and start and end of bursts. Transient signals usually vary over time and you typically cannot predict the occurrence exactly.