Think DSP: Digital Signal Processing in Python

by Allen B. Downey

If you understand basic mathematics and know how to program with Python, youâ??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 theyâ??re applied in the real world. In the first chapter alone, youâ??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. Youâ??ll

Genres: Programming, Technology, Engineering, Computer Science, Music, Mathematics, Science

168 pages, Paperback

Published August 30, 2016

About the author

Allen Downey is a Professor Emeritus at Olin College and the author of a series of freetextbooks related to software and data science, including Think Python, Think Bayes, and Think Complexity, which are also published by O’Reilly Media. His blog, Probably Overthinking It, features articles on Bayesian probability and statistics. He holds a Ph.D. in computer science from U.C. Berkeley, and M.S. and B.S. degrees from MIT.

Reviews

[☘Misericordia☘ ⚡ϟ⚡⛈⚡☁ ❇️❤❣]

Free online version http://greenteapress.com/wp/think-dsp/

[Lennart]

This book teaches the fundamentals of DSP, often using audio as the signal. I liked that the book is short (only ~150 pages), fairly cheap, very pragmatic (some theory, but not too much, focused on understanding the basics and being able to put that knowledge to use) and comes with github repo with notebooks with prepared examples from the book. Indeed, for being so short it covers a lot of ground. I found that the topics were introduced in a way that was easy to follow. I really did like the structure of the book. I'm happy with the understanding I got to DSP even without doing the exercises.
Initially I didn't like that the author has made his own ThinkDSP python library but after a while I saw the benefit. The book introduces the library, how to use it, and then the rest of the book benefits from the compact code due to the library.
In short, I recommend the book as an intro to DSP.

[Elie De Brauwer]

I enjoyed reading this book, especially the first half of the book, in the second half the book went more into frequency domain analysis where I was actually hoping it was going to remain more applied to sound and music.

Personally I'm not such a big fan of the entire python abstraction layer that was constructed and during my reading I invested some time in diving a bit deeper in the numpy and scipy's myself.

[Fedor]

Very pragmatic cookbook for DSP in Python. Without much of theory and full of practical implementations. Can be useful for research work and DSP software development. Don't forget to get Github repository with code examples.

[Risto Hinno]

Very nice intro to DSP. Explains basic concepts and shows code how to implement them. Easy to follow. Bonus is nicely refactored code which is easy to read. If you want to get quick intro to DSP this is a book for you.

[Fathima Mujahidha]

What an intro to DSP. basic concepts and shows code how to implement them explaining well. Easy to understand. Bonus is nicely refactored code which is easy to read. If you want to get quick intro to DSP this is a book for you.

[Anılbey]

I was looking for a resource to recap some of the concepts I've leant from the DSP class. This book helped!

[sbs transit]

#nsreads 34

Too proprietary to be much good

[Mohammad Abdelsalam]

Good for novice signals and systems students.