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Erschienen in:
Introduction Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

2. Audio Acquisition, Representation and Storage

verfasst von : Francesco Camastra, Alessandro Vinciarelli

Erschienen in: Machine Learning for Audio, Image and Video Analysis

Verlag: Springer London

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Abstract

What the reader should know to understand this chapter \(\bullet \) Basic notions of physics. \(\bullet \) Basic notions of calculus (trigonometry, logarithms, exponentials, etc.)

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Vorheriges Kapitel Introduction
Nächstes Kapitel Image and Video Acquisition, Representation and Storage
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
Since the implementation of a low-pass filter that actually stops all frequencies above a certain threshold is not possible, it is more correct to say that the effects of the aliasing problem are reduced to a level that does not disturb human perception. See [15] for a more extensive description of this issue.
 
2
There is no noticeable difference between the performance of the two companders, the A-law compander is used in Europe and other countries affiliated to the ITU (with \(A=87.56\)), while the \(\mu \)-law compander is mostly used in the USA (with \(\mu =255\)).
 
3
The results can be found on www.apple.com/quicktime/technologies/aac/.
 
4
The advantages of this property are particularly evident in the frequency domain. In fact, the Fourier transform of a convolution between two signals corresponds to the product between the Fourier transforms of the single signals, and this simplifies significantly the analysis of the effect of a system in the frequency domain.
 
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Metadaten
Titel
Audio Acquisition, Representation and Storage
verfasst von
Francesco Camastra
Alessandro Vinciarelli
Copyright-Jahr
2015
Verlag
Springer London
Buch
Machine Learning for Audio, Image and Video Analysis

Print ISBN: 978-1-4471-6734-1

Electronic ISBN: 978-1-4471-6735-8

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-1-4471-6735-8_2

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