Advances in the System of Higher-Dimension-Valued Neural Networks
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".
Deadline for manuscript submissions: 15 May 2024 | Viewed by 550
Special Issue Editors
Interests: octonion-valued neural networks; quaternion-valued neural networks; memristor-based neural networks; BAM neural networks and factional-order systems
Interests: neural network; memristor system; deep learning; intelligent control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent decades, the theory and technology of higher-dimension-valued neural networks have made great progress along with the rapid development of computing power and intelligent learning algorithms. Neural networks have developed and flourished in aspects such as signal processing, image operation, pattern recognition and so on. Today, the lower-dimension-valued neural networks can no longer meet the increasing demands of the real world. Therefore, systems of higher-dimension-valued neural networks, such as complex-valued, quaternion-valued ones or octonion-valued networks, are gaining traction because they can be applied in more areas.
In addition to the theoretical improvements, neural networks have also undergone certain enhancements in hardware. Hence, some scholars have proposed the use of memristor, which possesses both the unique memristance features and the common circuit characteristics, to build more practical neural networks.
This Special Issue welcomes submissions of original research articles and reviews. Research areas may include (but not limited to) the following:
(1) Dynamic analysis for fractional-order neural networks;
(2) Dynamic analysis and scientific application for memristor-based neural networks;
(3) Stability analysis;
(4) Complex-valued neural networks;
(5) Quaternion-valued neural networks;
(6) Octonion-valued neural networks;
(7) Synchronization and controllers;
(8) Deep learning theory and applications;
(9) Pattern recognition;
(10) Fuzzy logic;
(11) Image processing；
(12) Complex systems.
Dr. Jianying Xiao
Prof. Dr. Shiping Wen
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- neural network
- memristor system
- fractional-order system
- stability
- controllers
