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

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

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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