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Mathematics
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Advances of Intelligent Systems
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Special Issue "Advances of Intelligent Systems"

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 1573

Special Issue Editors

Prof. Dr. Fangfei Li
E-Mail Website
Guest Editor
School of Mathematics and the Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
Interests: cyber–physical systems; intelligent systems; Boolean networks; cyber security; estimation; deep learning; deep reinforcement learning
Dr. Jiapeng Xu

E-Mail
Co-Guest Editor
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada
Interests: event-triggered state estimation; risk-sensitive filtering; distributed filtering; hidden Markov models

Special Issue Information

Dear Colleagues,

Intelligent systems are widely used in power grids, air and road traffic control systems, communication networks and other practical applications. The rapid development of information technology and big data in recent years has brought about opportunities for the modeling, analysis, calculation, control and optimization of intelligent systems. Intelligent systems and computing, a multi-disciplinary subject, integrates simulation and computer modeling, data analysis, control theory, intelligent optimization, network technology and so on.

This Special Issue aims to publish new theories, methods, algorithms and applications pertaining to the analysis, calculation, optimization and control of intelligent systems. Topics of interest include, but are not limited to, the following:

  • Modeling in intelligent systems;
  • Simulation software;
  • Numerical methods for intelligent systems;
  • Optimization methods;
  • Control problems;
  • Markov decision process;
  • Reinforcement learning;
  • Deep learning.

Prof. Dr. Fangfei Li
Dr. Jiapeng Xu
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. Mathematics 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 2600 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

  • intelligent systems
  • reinforcement learning
  • deep learning
  • optimization methods

Published Papers (2 papers)

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Article
Mean Square Exponential Stability of Stochastic Delay Differential Systems with Logic Impulses
by
Chunxiang Li
,
Lijuan Shen
,
Fangshu Hui
,
Wen Luo
and
Zhongliang Wang
Mathematics 2023, 11(7), 1613; https://doi.org/10.3390/math11071613 - 27 Mar 2023
Viewed by 518
Abstract
This paper focuses on the mean square exponential stability of stochastic delay differential systems with logic impulses. Firstly, a class of nonlinear stochastic delay differential systems with logic impulses is constructed. Then, the logic impulses are transformed into an equivalent algebraic expression by [...] Read more.
This paper focuses on the mean square exponential stability of stochastic delay differential systems with logic impulses. Firstly, a class of nonlinear stochastic delay differential systems with logic impulses is constructed. Then, the logic impulses are transformed into an equivalent algebraic expression by using the semi-tensor product method. Thirdly, the mean square exponential stability criteria of nonlinear stochastic delay differential systems with logic impulses are given. Finally, two kinds of stochastic delay differential systems with logic impulses and uncertain parameters are discussed, and the coefficient conditions guaranteeing the mean square exponential stability of these systems are obtained. Full article
(This article belongs to the Special Issue Advances of Intelligent Systems)
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Article
Exponential Stability of Switched Neural Networks with Partial State Reset and Time-Varying Delays
by
Han Pan
,
Wenbing Zhang
and
Luyang Yu
Mathematics 2022, 10(20), 3870; https://doi.org/10.3390/math10203870 - 18 Oct 2022
Viewed by 689
Abstract
This paper mainly investigates the exponential stability of switched neural networks (SNNs) with partial state reset and time-varying delays, in which partial state reset means that only a fraction of the states can be reset at each switching instant. Moreover, both stable and [...] Read more.
This paper mainly investigates the exponential stability of switched neural networks (SNNs) with partial state reset and time-varying delays, in which partial state reset means that only a fraction of the states can be reset at each switching instant. Moreover, both stable and unstable subsystems are also taken into account and therefore, switched systems under consideration can take several switched systems as special cases. The comparison principle, the Halanay-like inequality, and the time-dependent switched Lyapunov function approach are used to obtain sufficient conditions to ensure that the considered SNNs with delays and partial state reset are exponentially stable. Numerical examples are provided to demonstrate the reliability of the developed results. Full article
(This article belongs to the Special Issue Advances of Intelligent Systems)
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