Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures

Milton Garces

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preprints.org > computer science and mathematics > applied mathematics > 202007.0292.v4

Working Paper Article Version 4 This version is not peer-reviewed

Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures

Milton Garces

Version 1 : Received: 9 July 2020 / Approved: 14 July 2020 / Online: 14 July 2020 (05:49:04 CEST)
Version 2 : Received: 14 July 2020 / Approved: 16 July 2020 / Online: 16 July 2020 (06:07:48 CEST)
Version 3 : Received: 10 August 2020 / Approved: 11 August 2020 / Online: 11 August 2020 (04:21:09 CEST)
Version 4 : Received: 13 August 2020 / Approved: 14 August 2020 / Online: 14 August 2020 (10:14:30 CEST)
Version 5 : Received: 18 August 2020 / Approved: 20 August 2020 / Online: 20 August 2020 (08:27:31 CEST)
Version 6 : Received: 25 August 2020 / Approved: 25 August 2020 / Online: 25 August 2020 (11:43:32 CEST)
Version 7 : Received: 29 August 2020 / Approved: 3 September 2020 / Online: 3 September 2020 (04:28:24 CEST)

A peer-reviewed article of this Preprint also exists.

Garcés, M.A. Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures. Entropy 2020, 22, 936. Garcés, M.A. Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures. Entropy 2020, 22, 936.

Abstract

Data acquisition by uncalibrated, heterogeneous digital sensor systems such as smartphones present emerging signal processing challenges. Binary metrics are proposed for the quantification of cyber-physical signal characteristics and features, and a highly standardized constant-Q variation of the Gabor atom is developed for use with wavelet transforms. Two different CWT reconstruction schemas are presented and tested under different SNR conditions. A sparse representation of the Nth order Gabor atoms worked well against a test blast synthetic using the wavelet entropy and a comparable entropy-like parametrization of the SNR as the CWT coefficient-weighting functions. The proposed methods should be well suited for dictionary-based machine learning.

Keywords

Gabor atoms; wavelet entropy; binary metrics; acoustics; quantum wavelet

Subject

Computer Science and Mathematics, Applied Mathematics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Comment 1

Received: 14 August 2020
Commenter: Milton Garces
Commenter's Conflict of Interests: Author

Comment: Updated and restructured after the first round of reviews.

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