Think DSP: Digital Signal Processing in Python (Paperback)

Allen B. Downey

Think DSP: Digital Signal Processing in Python (Paperback)

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商品描述

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.

商品描述(中文翻譯)

如果你懂得基本數學並且能夠使用Python進行編程，那麼你就準備好深入研究信號處理了。儘管大多數資源都從理論開始教授這個複雜的主題，但這本實用書籍通過展示這些技術在現實世界中的應用來介紹這些技術。僅在第一章中，你就能夠將聲音分解為其諧波，修改諧波並生成新的聲音。

作者Allen Downey解釋了譜分解、濾波、卷積和快速傅立葉變換等技術。本書還提供練習和代碼示例，以幫助你理解材料。

你將探索以下內容：

- 周期信號及其頻譜
- 簡單波形的諧波結構
- 鳴聲和其他頻譜隨時間變化的聲音
- 噪聲信號和噪聲的自相關函數
- 用於估計音高的自相關函數
- 用於壓縮的離散餘弦變換（DCT）
- 用於頻譜分析的快速傅立葉變換
- 時間操作與頻率域中的濾波器之間的關係
- 線性時不變（LTI）系統理論
- 在廣播中使用的振幅調製（AM）

本系列的其他書籍還包括Allen Downey的《Think Stats》和《Think Bayes》。

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