Alaa Sagheer
A Novel Autonomous Perceptron Model for Pattern Classification Applications
Sagheer, Alaa; Zidan, Mohammed; Abdelsamea, Mohammed M.
Authors
Mohammed Zidan
Mohammed M. Abdelsamea
Abstract
Pattern classification represents a challenging problem in machine learning and data science research domains, especially when there is a limited availability of training samples. In recent years, artificial neural network (ANN) algorithms have demonstrated astonishing performance when compared to traditional generative and discriminative classification algorithms. However, due to the complexity of classical ANN architectures, ANNs are sometimes incapable of providing efficient solutions when addressing complex distribution problems. Motivated by the mathematical definition of a quantum bit (qubit), we propose a novel autonomous perceptron model (APM) that can solve the problem of the architecture complexity of traditional ANNs. APM is a nonlinear classification model that has a simple and fixed architecture inspired by the computational superposition power of the qubit. The proposed perceptron is able to construct the activation operators autonomously after a limited number of iterations. Several experiments using various datasets are conducted, where all the empirical results show the superiority of the proposed model as a classifier in terms of accuracy and computational time when it is compared with baseline classification models.
Citation
Sagheer, A., Zidan, M., & Abdelsamea, M. M. (2019). A Novel Autonomous Perceptron Model for Pattern Classification Applications. Entropy, 21(8), https://doi.org/10.3390/e21080763
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 30, 2019 |
Online Publication Date | Aug 6, 2019 |
Publication Date | Aug 6, 2019 |
Deposit Date | Sep 26, 2019 |
Publicly Available Date | Sep 26, 2019 |
Journal | Entropy |
Electronic ISSN | 1099-4300 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 21 |
Issue | 8 |
Article Number | 763 |
DOI | https://doi.org/10.3390/e21080763 |
Keywords | General Physics and Astronomy |
Public URL | https://nottingham-repository.worktribe.com/output/2663354 |
Publisher URL | https://www.mdpi.com/1099-4300/21/8/763 |
Files
A Novel Autonomous Perceptron Model for Pattern Classification Applications
(501 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search