Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)-image
Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)-image
Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)-image
Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)-image
Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)-image

Think DSP: Digital Signal Processing in Python by Allen Downey (2016 Paperback)

$ 2.64

Language: English Publication Name: Think DSP : Digital Signal Processing in Python Type: Textbook Dewey Edition: 23 ISBN-10: 1491938455 Number of Pages: 168 Pages Author: Allen Downey brand: O'reilly Media, Incorporated Item Weight: 21.5 Oz Publisher: O'reilly Media, Incorporated Item Height: 0.7 in Format: Trade Paperback Publication Year: 2016 Item Length: 9.5 in Subject: Signals & Signal Processing, Programming / Open Source, Electrical, Programming Languages / Python Item Width: 7.2 in Dewey Decimal: 621.3822 ISBN-13: 9781491938454 gtin13: 9781491938454 LC Classification Number: TK5102.9 LCCN: 2016-439912 Subject Area: Computers, Technology & Engineering Illustrated: Yes Intended Audience: Scholarly & Professional Synopsis: 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., 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.

Description

  1. This book is a fantastic introduction to DSP with Python! The explanations are clear, the examples are practical, and the hands-on approach makes learning easy. Perfect for beginners and those looking to apply DSP concepts in real-world projects. Highly recommended!

    Harshit Pandey

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