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Xinxin Zhang,Peifeng Niu,Nan Liu,Guoqiang Li 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.2
This paper deals with the synchronization issue of fractional-order complex-valued Hopfield neural networkswith time delay. In this paper, by means of properties of the fractional-order inequality, such as H¨ olderinequality and Gronwall inequality, sufficient conditions are presented to guarantee the finite-time synchronizationof the fractional-order complex-valued delayed neural networks when 1=2 g < 1 and 0 <g < 1=2. Finally, twonumerical simulations are provided to show the effectiveness of the obtained results.
Runan Guo,Ziye Zhang,Chong Lin,Yuming Chu,Yongmin Li 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.3
This paper considers the finite time state estimation problem of complex-valued bidirectional associativememory (BAM) neutral-type neural networks with time-varying delays. By resorting to the Lyapunov functionapproach, the Wirtinger inequality and the reciprocally convex approach, a delay-dependent criterion in terms ofLMIs is established to guarantee the finite-time boundedness of the error-state system for the addressed system. Meanwhile, an effective state estimator is designed to estimate the network states through the available outputmeasurements. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed results.
Lan Yao,Zhen Wang,Qingbiao Wang,Jianwei Xia,Hao Shen 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.7
In this paper, the exponential stabilization of delayed complex-valued neural networks (DCNNs) is addressed via sampled-data control. First, aperiodic sampled-data control aimed at further reducing the frequency of data transmission is adopted, which covers the periodic sampling as a special case. Then, a free-matrix-based timedependent Lyapunov functional is specially constructed for stability analysis of closed-loop DCNNs, in which two extra free matrices are introduced and the available information of system states at the sampling instants are fullyutilized. Accordingly, some less conservative stability conditions are established. By resorting to a matrix transformation, the design scheme for the feedback gains can be obtained. Meanwhile, the qualitative relationship between the decay rate and the upper bound of the variable sampling period is established and the maximum allowable value of the variable sampling period is determined. Finally, an illustrative example is provided to demonstrate the feasibility of the proposed stabilization criteria.
Jingshun Cheng,Hai Zhang,Weiwei Zhang,Hongmei Zhang 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.5
Without decomposing the complex-valued systems into two real-valued subsystems, this paper investigates quasi-projective synchronization (QPS) problem for Caputo type fractional-order complex-valued neural networks (FOCVNNs) with mixed delays by choosing suitable controllers. To realize QPS, the linear feedback controller and adaptive feedback controller are designed, by constructing suitable Lyapunov function, utilizing the fractional Razumikhin theorem and the properties of Mittag-Leffler function and inequality technique, and several sufficient criteria for QPS of FOCVNNs with mixed delays are derived. In addition, the upper bound of the error of QPS is estimated. Finally, two numerical examples are simulated to verify the effectiveness and feasibility of the proposed results.