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Grid-Based Decimation for Wavelet Transforms With Stably Invertible Implementation

delete2023-01-01
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OA
AI
N
Nicki Holighaus *
G
Günther Koliander
C
Clara Hollomey
F
Friedrich Pillichshammer
DOI:10.1109/TASLP.2023.3235197delete
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Abstract

Abstract

En 中文
The constant center frequency to bandwidth ratio (Q-factor) of wavelet transforms provides a very natural representation for audio data. However, invertible wavelet transforms have either required non-uniform decimation & mdash;leading to irregular data structures that are cumbersome to work with & mdash;or require excessively high oversampling with unacceptable computational overhead. Here, we present a novel decimation strategy for wavelet transforms that leads to stable representations with oversampling rates close to one and uniform decimation. Specifically, we show that finite implementations of the resulting representation are energy-preserving in the sense of frame theory. The obtained wavelet coefficients can be stored in a time-frequency matrix with a natural interpretation of columns as time frames and rows as frequency channels. This matrix structure immediately grants access to a large number of algorithms that are successfully used in time-frequency audio processing, but could not previously be used jointly with wavelet transforms. We demonstrate the application of our method in processing based on nonnegative matrix factorization, in onset detection, and in phaseless reconstruction.
Keywords:
Wavelet transforms
Transforms
Time-frequency analysis
Filter banks
Continuous wavelet transforms
Discrete wavelet transforms
Q-factor
Audio applications
low-discrepancy sequences
sampling methods
shift-invariant systems
signal reconstruction
uniform decimation
wavelet transforms

Journal

I
IEEE-ACM Transactions on Audio Speech and Language Processing
IF:
5.1
Papers:
2.6K
Citations:
1.1W

Organization

A
Austrian Academy of Sciences
Scholars:
5.0K
Papers: 4.0K
Citations: 8.2K
U
University of Vienna
Scholars:
1.7W
Papers: 1.6W
Citations: 40