Think DSP: Digital Signal Processing in Python (Paperback)
暫譯: 思考數位信號處理：使用 Python 的數位信號處理

Allen B. Downey

Think DSP: Digital Signal Processing in Python (Paperback)

買這商品的人也買了...

相關主題

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)

如果您了解基本數學並且知道如何使用 Python 編程，那麼您已經準備好深入信號處理。雖然大多數資源從理論開始教授這個複雜的主題，但這本實用的書籍通過展示技術在現實世界中的應用來介紹這些技術。在第一章中，您將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 解釋了諸如頻譜分解、濾波、卷積和快速傅立葉變換（Fast Fourier Transform）的技術。這本書還提供了練習和代碼示例，以幫助您理解材料。

您將探索：

- 週期信號及其頻譜
- 簡單波形的諧波結構
- 隨時間變化頻譜的啁啾聲和其他聲音
- 噪聲信號和自然噪聲來源
- 用於估計音高的自相關函數
- 用於壓縮的離散餘弦變換（Discrete Cosine Transform, DCT）
- 用於頻譜分析的快速傅立葉變換（Fast Fourier Transform）
- 將時間域中的操作與頻域中的濾波器相關聯
- 線性時不變（Linear Time-Invariant, LTI）系統理論
- 用於無線電的幅度調變（Amplitude Modulation, AM）

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

類似商品