Wei Wei Zhang, Hai Zhang, Jinde Cao, Fuad E. Alsaadi et al.
This paper considers the global asymptotical synchronization of fractional-order memristive complex-valued neural networks (FOMCVNN), with both parameter uncertainties and multiple time delays. Sufficient conditions of uncertain FOMCVNN, with multiple time delays, are established through the employm...
Xiangyong Chen, Tingwen Huang, Jinde Cao, Ju H. Park et al.
This study mainly investigates finite‐time multi‐switching synchronisation of multiple uncertain complex chaotic systems with network transmission mode. Both the unknown parameters and disturbances are considered. By establishing the desired multi‐switching rules, the definition of finite‐time hybri...
R. Rakkiyappan, R. Sivaranjani, G. Velmurugan, Jinde Cao
In this paper, the problem of the global O(t(-α)) stability and global asymptotic periodicity for a class of fractional-order complex-valued neural networks (FCVNNs) with time varying delays is investigated. By constructing suitable Lyapunov functionals and a Leibniz rule for fractional differentiat...
Ruoxia Li, Jinde Cao
Dissipativity theory is a very important concept in the field of control system. In this paper, we pay attention to the problem of dissipativity analysis of memristive neural networks with time‐varying delay and randomly occurring uncertainties(ROUs). Under the framework of Filippov solution, differ...
Hai Zhang, Renyu Ye, Jinde Cao, Alsaedi Ahmed et al.
Abstract This paper is concerned with the globally asymptotic stability of the Riemann‐Liouville fractional‐order neural networks with time‐varying delays. The Lyapunov functional approach to stability analysis for nonlinear fractional‐order functional differential equations is discussed. By constru...
Ning Li, Jinde Cao
This paper is concerned with passivity and robust synchronisation of switched coupled neural networks with uncertain parameters. First, the mathematical model of switched coupled neural networks with interval uncertain parameters is established, which consists of L modes and switches from one mode t...
Tao Wu, Jinde Cao, Lianglin Xiong, Haiyang Zhang
This paper investigates the problem of stabilization for semi‐Markov chaotic systems with fuzzy sampled‐data controllers, in which the semi‐Markov jump has generally uncertain transition rates. The exponential stability condition is firstly obtained by the following two main techniques: To make full...
Jianhua Guo, Zhao Liu, Wei Huang, Yun Wei et al.
Short‐term traffic flow forecasting has been regarded as essential for intelligent transportation systems, including both point prediction and interval prediction. Compared with point prediction, interval prediction of traffic flow in the future will be critical for traffic managers to make reasonab...
Zhengwen Tu, Jinde Cao, Ahmed Alsaedi, Fuad E. Alsaadi et al.
In this article, the problem of global exponential stability in Lagrange sense of neutral type complex‐valued neural networks (CVNNs) with delays is investigated. Two different classes of activation functions are considered, one can be separated into real part and imaginary part, and the other canno...
Chengdong Yang, Haibo He, Tingwen Huang, Ancai Zhang et al.
There is spatio‐temporal nature for many multi‐agent systems such as infight hose‐and‐drogue aerial refuelling systems. To deal with consensus control of such cases, this study establishes a non‐linear leader‐following spatio‐temporal multi‐agent system modelled by partial differential equations. In...
Zhang Bingjie, Yusong Liu, Jinde Cao, Shujun Wu et al.
Conjugate gradient method has been verified to be one effective strategy for training neural networks due to its low memory requirements and fast convergence. In this paper, we propose an efficient conjugate gradient method to train fully complex-valued network models in terms of Wirtinger different...
Hao Wu, Qimin Zhou, Rencan Nie, Jinde Cao
In recommender systems, matrix factorization and its variants have grown up to be dominant in collaborative filtering due to their simplicity and effectiveness. In matrix factorization based methods, dot product which is actually used as a measure of distance from users to items, does not satisfy th...
R. Manivannan, Sidhartha Panda, Kil To Chong, Jinde Cao
The issue of unified dissipativity-based Arcak-type state estimator design for delayed static neural networks (SNNs) with leakage term and noise distraction was considered here. An Arcak-type state observer, which is compact than the usually used Luenberger-type state estimator, is selected to imple...
Jinren Zhang, Jinde Cao, Wei Huang, Xinli Shi et al.
The Rutting prediction model is an essential element of efficient pavement management systems. Accuracy of commonly used predictive model necessitates knowledge of the input parameters that was incorporated and local calibration of the model coefficients. In this paper, a novel rutting prediction mo...
Xiaoxiao Lv, Xiaodi Li, Jinde Cao, Peiyong Duan
The problem of exponential synchronization for neural networks is investigated via feedback control in complex environment. By constructing suitable Lyapunov‐Krasovskii functionals and applying the piecewise analytic method, some sufficient criteria for exponential synchronization of the addressed n...