A review of dynamics analysis of neural networks and applications in creation psychology

被引:0
作者
Yin, Xiangwen [1 ]
机构
[1] Shandong Normal Univ, Sch Chinese Language & Literature, Jinan 250014, Peoples R China
来源
ELECTRONIC RESEARCH ARCHIVE | 2023年 / 31卷 / 05期
关键词
review; synchronization; stability; stabilization; memristive neural networks; reaction-diffusion neural networks; creation psychology; TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY; ALMOST-PERIODIC SOLUTIONS; MIXED DELAYS; IMPULSIVE SYNCHRONIZATION; FEEDBACK SYNCHRONIZATION; ASYMPTOTIC STABILITY; STABILIZATION; MODEL; SYSTEM;
D O I
10.3934/era.2023132
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The synchronization problem and the dynamics analysis of neural networks have been thoroughly explored, and there have been many interesting results. This paper presents a review of the issues of synchronization problem, the periodic solution and the stability/stabilization with emphasis on the memristive neural networks and reaction-diffusion neural networks. First, this paper introduces the origin and development of neural networks. Then, based on different types of neural networks, some synchronization problems and the design of the controllers are introduced and summarized in detail. Some results of the periodic solution are discussed according to different neural networks, including bi-directional associative memory (BAM) neural networks and cellular neural networks. From the perspective of memristive neural networks and reaction-diffusion neural networks, some results of stability and stabilization are reviewed comprehensively with latest progress. Based on a review of dynamics analysis of neural networks, some applications in creation psychology are also introduced. Finally, the conclusion and the future research directions are provided.
引用
收藏
页码:2595 / 2625
页数:31
相关论文
共 163 条
[1]   Fixe d/pre define d-time lag synchronization of complex-valued BAM neural networks with stochastic perturbations [J].
Abdurahman, Abdujelil ;
Abudusaimaiti, Mairemunisa ;
Jiang, Haijun .
APPLIED MATHEMATICS AND COMPUTATION, 2023, 444
[2]   CHAOTIC NEURAL NETWORKS [J].
AIHARA, K ;
TAKABE, T ;
TOYODA, M .
PHYSICS LETTERS A, 1990, 144 (6-7) :333-340
[3]   Finite Time Stability Analysis of Fractional-Order Complex-Valued Memristive Neural Networks with Proportional Delays [J].
Ali, M. Syed ;
Narayanan, G. ;
Orman, Zeynep ;
Shekher, Vineet ;
Arik, Sabri .
NEURAL PROCESSING LETTERS, 2020, 51 (01) :407-426
[4]   Passivity-based synchronization of Markovian jump complex dynamical networks with time-varying delays, parameter uncertainties, reaction-diffusion terms, and sampled-data control [J].
Ali, M. Syed ;
Palanisamy, L. ;
Yogambigai, J. ;
Wang, Linshan .
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2019, 352 :79-92
[5]   Pull-in Phenomenon in the Electrostatically Micro-switch Suspended between Two Conductive Plates using the Artificial Neural Network [J].
Aliasghary, Mortaza ;
Mobki, Hamed ;
Ouakad, Hassen M. .
JOURNAL OF APPLIED AND COMPUTATIONAL MECHANICS, 2022, 8 (04) :1222-1235
[6]  
[Anonymous], 1969, Perceptrons: An Introduction to Computational Geometry
[7]   On the global asymptotic stability of delayed cellular neural networks [J].
Arik, S ;
Tavsanoglu, V .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 2000, 47 (04) :571-574
[8]  
Aubin J. P., 2012, Differential Inclusions: Set-valued Maps and Viability Theory
[9]   Attractiveness of pseudo almost periodic solutions for delayed cellular neural networks in the context of measure theory [J].
Bekolle, David ;
Ezzinbi, Khalil ;
Fatajou, Samir ;
Danga, Duplex Elvis Houpa ;
Besseme, Fritz Mbounja .
NEUROCOMPUTING, 2021, 435 (435) :253-263
[10]   Finite-/fixed-time synchronization of delayed Clifford-valued recurrent neural networks [J].
Boonsatit, N. ;
Rajchakit, G. ;
Sriraman, R. ;
Lim, C. P. ;
Agarwal, P. .
ADVANCES IN DIFFERENCE EQUATIONS, 2021, 2021 (01)