Audio Compression using Periodic Gabor with Biorthogonal Exchange: Implementation Using the Zak Transform

Fuente: arXiv
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Autori principali: Alimi, Roger, Tannor, David J.
Natura: Preprint
Pubblicazione: 2025
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author Alimi, Roger
Tannor, David J.
author_facet Alimi, Roger
Tannor, David J.
contents An efficient new approach to signal compression is presented based of a novel variation on the Gabor basis set. Following earlier work by Shimshovitz and Tannor, we convolve the conventional Gabor functions with Dirichlet functions to obtain a Periodic Gabor basis set (PG). The PG basis is exact for continuous functions that are periodic band-limited. Using the orthonormality of the Dirichlet functions, the calculation of the PG coefficients becomes trivial and numerically stable, but its representation does not allow compression. Large compression factors are achieved by exchanging the PG basis with its biorthogonal basis, thereby using the localized PG basis to calculate the coefficients (PGB). Here we implement the PGB formalism using the Fast Zak Transform and obtain very high efficiency with respect to both CPU and memory. We compare the method with the state of the art Short-Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT) methods on a variety of audio files, including music and speech samples. In all cases tested our scheme surpasses the STFT by far and in most cases outperforms DWT.
format Preprint
id arxiv_https___arxiv_org_abs_2503_22703
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Audio Compression using Periodic Gabor with Biorthogonal Exchange: Implementation Using the Zak Transform
Alimi, Roger
Tannor, David J.
Audio and Speech Processing
Sound
Signal Processing
An efficient new approach to signal compression is presented based of a novel variation on the Gabor basis set. Following earlier work by Shimshovitz and Tannor, we convolve the conventional Gabor functions with Dirichlet functions to obtain a Periodic Gabor basis set (PG). The PG basis is exact for continuous functions that are periodic band-limited. Using the orthonormality of the Dirichlet functions, the calculation of the PG coefficients becomes trivial and numerically stable, but its representation does not allow compression. Large compression factors are achieved by exchanging the PG basis with its biorthogonal basis, thereby using the localized PG basis to calculate the coefficients (PGB). Here we implement the PGB formalism using the Fast Zak Transform and obtain very high efficiency with respect to both CPU and memory. We compare the method with the state of the art Short-Time Fourier Transform (STFT) and Discrete Wavelet Transform (DWT) methods on a variety of audio files, including music and speech samples. In all cases tested our scheme surpasses the STFT by far and in most cases outperforms DWT.
title Audio Compression using Periodic Gabor with Biorthogonal Exchange: Implementation Using the Zak Transform
topic Audio and Speech Processing
Sound
Signal Processing
url https://arxiv.org/abs/2503.22703