Think DSP: Digital Signal Processing in Python

If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds.

Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material.

You’ll explore:

Periodic signals and their spectrums
Harmonic structure of simple waveforms
Chirps and other sounds whose spectrum changes over time
Noise signals and natural sources of noise
The autocorrelation function for estimating pitch
The discrete cosine transform (DCT) for compression
The Fast Fourier Transform for spectral analysis
Relating operations in time to filters in the frequency domain
Linear time-invariant (LTI) system theory
Amplitude modulation (AM) used in radio
Other books in this series include Think Stats and Think Bayes, also by Allen Downey.