Chapter 10. Signal Processing

In this chapter, we will cover the following topics:

  • Analyzing the frequency components of a signal with a Fast Fourier Transform
  • Applying a linear filter to a digital signal
  • Computing the autocorrelation of a time series


Signals are mathematical functions that describe the variation of a quantity across time or space. Time-dependent signals are often called time series. Examples of time series include share prices, which are typically presented as successive points in time spaced at uniform time intervals. In physics or biology, experimental devices record the evolution of variables such as electromagnetic waves or biological processes.

In signal processing, a general objective consists of extracting meaningful ...

Get IPython Interactive Computing and Visualization Cookbook - Second Edition now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.