Article
Version 7
This version is not peer-reviewed
Quantized Constant-Q Gabor Atoms for Sparse Binary Representations of Cyber-Physical Signatures
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)
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
Increased data acquisition by uncalibrated, heterogeneous digital sensor systems such as smartphones present new challenges. Binary metrics are proposed for the quantification of cyber-physical signal characteristics and features, and a standardized constant-Q variation of the Gabor atom is developed for use with wavelet transforms. Two different continuous wavelet transform (CWT) reconstruction formulas are presented and tested under different signal to noise ratio (SNR) conditions. A sparse superposition of Nth order Gabor atoms worked well against a synthetic blast transient using the wavelet entropy and an entropy-like parametrization of the SNR as the CWT coefficient-weighting functions. The proposed methods should be well suited for sparse feature extraction and dictionary-based machine learning across multiple sensor modalities.
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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