A Comprehensive Review of Continuous-/Discontinuous-Time Fractional-Order Multidimensional Neural Networks

被引:17
作者
Cao, Jinde [1 ,2 ,3 ]
Udhayakumar, K. [4 ,5 ]
Rakkiyappan, R. [6 ]
Li, Xiaodi [7 ]
Lu, Jianquan [8 ]
机构
[1] Southeast Univ, Sch Math, Frontiers Sci Ctr Mobile Informat Commun & Secur, Nanjing 210096, Peoples R China
[2] Purple Mt Labs, Nanjing 211111, Peoples R China
[3] Yonsei Univ, Yonsei Frontier Lab, Seoul 03722, South Korea
[4] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India
[5] United Arab Emirates Univ, Dept Math Sci, Coll Sci, Al Ain, U Arab Emirates
[6] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India
[7] Shandong Normal Univ, Sch Math & Stat, Jinan 250014, Peoples R China
[8] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
关键词
Artificial neural networks; Synchronization; Mathematics; Delays; Stability criteria; Quaternions; Fractional calculus; Complex field; dynamical networks; fractional-order neural networks (FONNs); octonion field; quaternion field; stability; synchronization; MITTAG-LEFFLER STABILITY; GLOBAL EXPONENTIAL STABILITY; FINITE-TIME; SYNCHRONIZATION ANALYSIS; QUASI-SYNCHRONIZATION; PROJECTIVE SYNCHRONIZATION; ADAPTIVE SYNCHRONIZATION; UNCERTAIN PARAMETERS; NONLINEAR DYNAMICS; ROBUST STABILITY;
D O I
10.1109/TNNLS.2021.3129829
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The dynamical study of continuous-/discontinuous-time fractional-order neural networks (FONNs) has been thoroughly explored, and several publications have been made available. This study is designed to give an exhaustive review of the dynamical studies of multidimensional FONNs in continuous/discontinuous time, including Hopfield NNs (HNNs), Cohen-Grossberg NNs, and bidirectional associative memory NNs, and similar models are considered in real (R), complex (C), quaternion (Q), and octonion (O) fields. Since, in practice, delays are unavoidable, theoretical findings from multidimensional FONNs with various types of delays are thoroughly evaluated. Some required and adequate stability and synchronization requirements are also mentioned for fractional-order NNs without delays.
引用
收藏
页码:5476 / 5496
页数:21
相关论文
共 203 条
[11]   State estimation of fractional-order delayed memristive neural networks [J].
Bao, Haibo ;
Cao, Jinde ;
Kurths, Juergen .
NONLINEAR DYNAMICS, 2018, 94 (02) :1215-1225
[12]   Automatic musical instrument classification using fractional fourier transform based- MFCC features and counter propagation neural network [J].
Bhalke, D. G. ;
Rao, C. B. Rama ;
Bormane, D. S. .
JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2016, 46 (03) :425-446
[13]  
Boroomand A, 2009, LECT NOTES COMPUT SC, V5506, P883, DOI 10.1007/978-3-642-02490-0_108
[14]   Insulin-Like Growth Factor 1 Receptor and Response to Anti-IGF1R Antibody Therapy in Osteosarcoma [J].
Cao, Yu ;
Roth, Michael ;
Piperdi, Sajida ;
Montoya, Kristofer ;
Sowers, Rebecca ;
Rao, Pulivarthi ;
Geller, David ;
Houghton, Peter ;
Kolb, E. Anders ;
Gill, Jonathan ;
Gorlick, Richard .
PLOS ONE, 2014, 9 (08)
[15]   The Optimization of Synchronization Control Parameters for Fractional-Order Delayed Memristive Neural Networks Using SIWPSO [J].
Chang, Qi ;
Hu, Aihua ;
Yang, Yongqing ;
Li, Li .
NEURAL PROCESSING LETTERS, 2020, 51 (02) :1541-1556
[16]   Finite-time Mittag-Leffler synchronization of fractional-order delayed memristive neural networks with parameters uncertainty and discontinuous activation functions [J].
Chen, Chong ;
Ding, Zhixia ;
Li, Sai ;
Wang, Liheng .
CHINESE PHYSICS B, 2020, 29 (04)
[17]   Global Uniform Asymptotic Fixed Deviation Stability and Stability for Delayed Fractional-order Memristive Neural Networks with Generic Memductance [J].
Chen, Jiejie ;
Chen, Boshan ;
Zeng, Zhigang .
NEURAL NETWORKS, 2018, 98 :65-75
[18]   O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations [J].
Chen, Jiejie ;
Chen, Boshan ;
Zeng, Zhigang .
NEURAL NETWORKS, 2018, 100 :10-24
[19]   Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks [J].
Chen, Jiejie ;
Zeng, Zhigang ;
Jiang, Ping .
NEURAL NETWORKS, 2014, 51 :1-8
[20]   Delay-dependent criterion for asymptotic stability of a class of fractional-order memristive neural networks with time-varying delays [J].
Chen, Liping ;
Huang, Tingwen ;
Tenreiro Machado, J. A. ;
Lopes, Antonio M. ;
Chai, Yi ;
Wu, Ranchao .
NEURAL NETWORKS, 2019, 118 :289-299