Think DSP: Digital Signal Processing in Python

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"O'Reilly Media, Inc.", 2016. 7. 12. - 168페이지

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.

 

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목차

Chapter 1 Sounds and Signals
1
Chapter 2 Harmonics
13
Chapter 3 NonPeriodic Signals
25
Chapter 4 Noise
39
Chapter 5 Autocorrelation
53
Chapter 6 Discrete Cosine Transform
65
Chapter 7 Discrete Fourier Transform
77
Chapter 8 Filtering and Convolution
91
Chapter 9 Differentiation and Integration
105
Chapter 10 LTI Systems
119
Chapter 11 Modulation and Sampling
133
Index
149
About the Author
153
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저자 정보 (2016)

Allen Downey is a Professor of Computer Science at Olin College of Engineering. He has taught at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT.

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