Think DSP: Digital Signal Processing in Python

Allen B. Downey

Version 1.1.4

Copyright 2014 Allen B. Downey

Permission is granted to copy, distribute, and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, which is available at http://creativecommons.org/licenses/by-nc-sa/4.0/.

• Preface
  • Who is this book for?
  • Using the code
  • Contributor List
• Sounds and signals
  • Periodic signals
  • Spectral decomposition
  • Signals
  • Reading and writing Waves
  • Spectrums
  • Wave objects
  • Signal objects
  • Exercises
• Harmonics
  • Triangle waves
  • Square waves
  • Aliasing
  • Computing the spectrum
  • Exercises
• Non-periodic signals
  • Linear chirp
  • Exponential chirp
  • Spectrum of a chirp
  • Spectrogram
  • The Gabor limit
  • Leakage
  • Windowing
  • Implementing spectrograms
  • Exercises
• Noise
  • Uncorrelated noise
  • Integrated spectrum
  • Brownian noise
  • Pink Noise
  • Gaussian noise
  • Exercises
• Autocorrelation
  • Correlation
  • Serial correlation
  • Autocorrelation
  • Autocorrelation of periodic signals
  • Correlation as dot product
  • Using NumPy
  • Exercises
• Discrete cosine transform
  • Synthesis
  • Synthesis with arrays
  • Analysis
  • Orthogonal matrices
  • DCT-IV
  • Inverse DCT
  • The Dct class
  • Exercises
• Discrete Fourier Transform
  • Complex exponentials
  • Complex signals
  • The synthesis problem
  • Synthesis with matrices
  • The analysis problem
  • Efficient analysis
  • DFT
  • The DFT is periodic
  • DFT of real signals
  • Exercises
• Filtering and Convolution
  • Smoothing
  • Convolution
  • The frequency domain
  • The convolution theorem
  • Gaussian filter
  • Efficient convolution
  • Efficient autocorrelation
  • Exercises
• Differentiation and Integration
  • Finite differences
  • The frequency domain
  • Differentiation
  • Integration
  • Cumulative sum
  • Integrating noise
  • Exercises
• LTI systems
  • Signals and systems
  • Windows and filters
  • Acoustic response
  • Systems and convolution
  • Proof of the Convolution Theorem
  • Exercises
• Modulation and sampling
  • Convolution with impulses
  • Amplitude modulation
  • Sampling
  • Aliasing
  • Interpolation
  • Exercises
• Index

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