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Filter Banks and Audio Coding

Compressing Audio Signals Using Python

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  • 212pages
  • 8 heures de lecture

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Focusing on audio coding fundamentals, this textbook integrates Python programming to illustrate principles and facilitate experiments. It begins with essential digital signal processing concepts, progressing to filter banks and their design methods. The author introduces psycho-acoustic models and guides readers in their implementation. Additionally, specialized components such as the Integer-to-Integer MDCT filter bank and predictive coding techniques for lossless and low-delay coding are covered, with practical Python examples throughout.

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Filter Banks and Audio Coding, Gerald Schuller

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Année de publication
2020
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