Book Description
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.
This open book is licensed under a Creative Commons License (CC BY-NC). You can download Think DSP ebook for free in PDF format (4.5 MB).
Table of Contents
Chapter 1
Sounds and Signals
Chapter 2
Harmonics
Chapter 3
NonPeriodic Signals
Chapter 4
Noise
Chapter 5
Autocorrelation
Chapter 6
Discrete Cosine Transform
Chapter 7
Discrete Fourier Transform
Chapter 8
Filtering and Convolution
Chapter 9
Differentiation and Integration
Chapter 10
LTI Systems
Chapter 11
Modulation and Sampling
Index