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

Milton Garces

Submit preprint
How it Works
Instructions for Authors
Subject Areas
Advisory Board
screening preprints
About
Statistics
Log in/Register

Instructions for Authors
Statistics
About
FAQ
Submit Log in/Register

Share this article with

Create alert

Email:

Load new image

preprints.org > mathematics & computer science > applied mathematics > 202007.0292.v6

Working Paper Article Version 6 This version is not peer-reviewed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.

DOI: 10.3390/e22090936

Cite as:

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

MATHEMATICS & COMPUTER SCIENCE, 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.

Download PDF

Comments (1)

Comment 1

Received: 25 August 2020
Commenter: Milton Garces
Commenter's Conflict of Interests: Author

Comment: Accepted 21 August. Final review version before proofs.

+ Respond to this comment

Your full name

Your affiliation information (e.g., name of your university/institution/organization)

Not displayed online.

Your Email address (not made public)

Importance: How significant is the paper to the field?

Outstanding/highlight paper

Significant contribution

Incremental contribution

No contribution

I am not qualified to judge

Soundness of evidence/arguments presented:

Conclusions well supported

Most conclusions supported (minor revision needed)

Incomplete evidence (major revision needed)

Hypothesis, unsupported conclusions, or proof-of-principle

I am not qualified to judge

Please leave your comment to this article below.

Mathematical equations can be typed in either LaTeX formats \\[ ... \\] or $$ ... $$, or MathML format <math> ... </math>. Try the LaTeX or MathML example.

Type equation:

Preview:

Copy equation into message below

Close menu

Please click a symbol to insert it into the message box below:

Please enter the link here:

Please enter a valid URL

Optionally, you can enter text that should appear as linked text:

Copy link into message below

Close menu

Please enter or paste the URL to the image here (please only use links to jpg/jpeg, png and gif images):

Please enter a valid URL

Copy image into message below

Close menu

Type author name or keywords to filter the list of references in this group (you can add a new citation under Bibliography):

No existing citations in Discussion Group

Wikify editor is a simple editor for wiki-style mark-up. It was written by MDPI for Sciforum in 2014. The rendering of the mark-up is based on Wiky.php with some tweaks. Rendering of mathematical equations is done with MathJax. Please send us a message for support or for reporting bugs.

Close menu

Please declare any conflicts of interest you may have with this paper, financial or otherwise.

I do not have a conflict of interest

I would like to declare a conflict of interest

Display my name on the website Send my name and email address to the authors I want to get recognition for my comment on Publons

[what’s this?]. Link your accounts here

Captcha

Renew

I accept the following conditions:

Comments must follow the standards of professional discourse and should focus on the scientific content of the article. Insulting or offensive language, personal attacks and off-topic remarks will not be permitted. Comments must be written in English. Preprints reserves the right to remove comments without notice. Readers who post comments are obliged to declare any competing interests, financial or otherwise.

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)

what’s this?

Add a record of this review to Publons to track and showcase your reviewing expertise across the world’s journals.

Downloads 0

Comments 1

Metrics 0

Get PDF Cite Share 0

Bookmark BibSonomy Mendeley Reddit Delicious

Alerts

Notify me about updates to this article or when a peer-reviewed version is published.

Preprints.org is a free preprint server subsidized by MDPI in Basel, Switzerland.

MDPI Initiatives

SciProfiles
Sciforum
Encyclopedia
MDPI Books
Scilit
Proceedings
JAMS

Important links

How it Works
Advisory Board
FAQ
Instructions for Authors
About

Choose the area that interest you and we will send you notifications of new preprints at your preferred frequency.

Disclaimer

We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.

RSS feed for

Preprints: The Multidisciplinary Preprint Platform

Paste the URL in your RSS reader:

https://www.preprints.org/rss

Please note that by using ScienceDirect RSS feeds, you agree to our Terms of Use and Privacy Policy.