共查询到20条相似文献，搜索用时 359 毫秒
1.
Jui-Pin Tseng 《Journal of The Franklin Institute》2018,355(14):6549-6578
This investigation establishes the global synchronization of an array of coupled memristor-based neural networks with delays. The coupled networks that are considered can incorporate both the internal delay in each individual network and the transmission delay across different networks. The coupling scheme, which consists of a nonlinear term and a sign term, is rather general. In particular, it can be asymmetric, and admits the coexistence of excitatory and inhibitory connections. Based on an iterative approach, the problem of synchronization is transformed into solving a corresponding linear system of algebraic equations. Subsequently, the respective synchronization criteria, which depend on whether the transmission delay exists, are derived respectively. Three examples are given to illustrate the effectiveness of the theories presented in this paper. The synchronization of the systems in two examples cannot be handled by existing techniques. 相似文献
2.
M.J. Park O.M. Kwon Ju H. Park S.M. Lee E.J. Cha 《Journal of The Franklin Institute》2012,349(5):1699-1720
This paper proposes new delay-dependent synchronization criteria for coupled stochastic neural networks with time-varying delays and leakage delay. By constructing a suitable Lyapunov–Krasovskii's functional and utilizing Finsler's lemma, novel synchronization criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by using the LMI toolbox in MATLAB. Three numerical examples are given to illustrate the effectiveness of the proposed methods. 相似文献
3.
This paper is concerned with master-slave synchronization for chaotic Lur'e systems subject to aperiodic sampled-data. To reduce the communication burden, an aperiodic event-triggered (APET) transmission scheme is introduced to determine the transmission of the latest sampling synchronization data. In order to reduce the design conservatism, a novel time-dependent Lyapunov functional (TDLF) is constructed to fully use the characteristics about sampling behavior, triggering error, and nonlinear part of the system, simultaneously. A more relaxed constraint criterion is then presented to ensure the positivity of the whole functional between two sampling instants. By partially resorting to the TDLF, the APET-based synchronization criterion depending on the upper and lower bounds of the uncertain sampling period is presented. The synchronization criterion based on aperiodic-sampling mechanism is also provided. Finally, a typical example about neural networks is offered to illustrate the benefit and validity of obtained synchronization methodologies. 相似文献
4.
Xiaolin Li 《Journal of The Franklin Institute》2008,345(7):779-791
In this paper, an adaptive feedback controller is designed to achieve complete synchronization of unidirectionally coupled delayed neural networks with stochastic perturbation. LaSalle-type invariance principle for stochastic differential delay equations is employed to investigate the globally almost surely asymptotical stability of the error dynamical system. An example and numerical simulation are given to demonstrate the effectiveness of the theory results. 相似文献
5.
In this paper, we study the synchronization problem of a class of chaotic neural networks with time-varying delays and unbounded distributed delays under stochastic perturbations. By using Lyapunov-Krasovskii functional, drive-response concept, output coupling with delay feedback and linear matrix inequality (LMI) approach, we obtain some sufficient conditions in terms of LMIs ensuring the exponential synchronization of the addressed neural networks. The feedback controllers can be easily obtained by solving the derived LMIs. Moreover, the main results are generalizations of some recent results reported in the literature. A numerical example is also provided to demonstrate the effectiveness and applicability of the obtained results. 相似文献
6.
Yanli Huang Weizhong Chen Shunyan Ren Zewei Zheng 《Journal of The Franklin Institute》2018,355(13):5968-5997
This paper investigate the generalized synchronization and pinning adaptive generalized synchronization for delayed coupled different dimensional neural networks with hybrid coupling, respectively. First, some sufficient conditions for reaching the generalized synchronization and pinning generalized synchronization of the considered network are acquired by using some inequality techniques and Lyapunov functional method. Second, because the precise parameter values of network cannot be obtained in some situations, we also purse the study on the generalized synchronization analysis and pinning control for the case of coupled different dimensional neural networks with parameter uncertainties. Third, two numerical examples are provided for substantiating the effectiveness of the derived results. 相似文献
7.
Xiaona Song Xingru Li Shuai Song Yijun Zhang Zhaoke Ning 《Journal of The Franklin Institute》2021,358(4):2482-2499
This paper investigates the quasi-synchronization of reaction-diffusion neural networks with hybrid coupling and parameter mismatches via sampled-data control technology. First, the models of neural networks with switching parameter and fraction Brownian motion are given. As a result of parameter mismatches, synchronization is normally not possible to realize directly, then the improved Halanay’s inequality is introduced, which is an important lemma to prove that the considered networks realize quasi-synchronization. Furthermore, based on stochastic theory, Lyapunov function method and inequality techniques, some sufficient conditions are derived to guarantee the quasi-synchronization of hybrid coupled neural networks with reaction-diffusion terms driven by fractional Brownian motion. Finally, two simulation examples are given to prove the efficiency of the developed criteria. 相似文献
8.
This paper is concerned with a class of neutral delay BAM neural networks with time-varying delays in leakage terms. Some sufficient conditions are established to ensure the existence and exponential stability for such class of neural networks by employing the exponential dichotomy of linear differential equations, fixed point theorems and differential inequality techniques. An example is provided to show the effectiveness of the theoretical results. The results of this paper are completely new and complementary to the previously known results. 相似文献
9.
In this paper, we concern the finite-time synchronization problem for delayed dynamical networks via aperiodically intermittent control. Compared with some correspondingly previous results, the intermittent control can be aperiodic which is more general. Moreover, by establishing a new differential inequality and constructing Lyapunov function, several useful criteria are derived analytically to realize finite-time synchronization for delay complex networks. Additionally, as a special case, some sufficient conditions ensuring the finite-time synchronization for a class of coupled neural network are obtained. It is worth noting that the convergence time is carefully discussed and does not depend on control widths or rest widths for the proposed aperiodically intermittent control. Finally, a numerical example is given to demonstrate the validness of the proposed scheme. 相似文献
10.
Mingwen Zheng Lixiang Li Haipeng Peng Jinghua Xiao Yixian Yang Yanping Zhang Hui Zhao 《Journal of The Franklin Institute》2018,355(14):6780-6809
This paper mainly investigates the fixed-time synchronization of memristor-based fuzzy cellular neural network (MFCNN) with time-varying delay. By utilizing differential inclusion, set-valued map theory, the definitions of finite-time and fixed-time stability, we convert the fixed-time synchronization control of the drive-response MFCNN into the equivalent fixed-time stability problem of the error system between the drive-response systems. Some novel sufficient conditions are derived to guarantee the fixed-time synchronization of the drive-response MFCNN based on a simple Lyapunov function and a nonlinear feedback controller. Meanwhile, the settling time can be estimated by simple calculations. Furthermore, these fixed-time synchronization criteria here are easy to validate and extend to the MFCNN without time-varying delay and general memristor-based neural networks. Finally, three numerical examples are given to illustrate the correctness of the main results. 相似文献
11.
This paper considers existence, uniqueness and the global asymptotic stability of fuzzy cellular neural networks with mixed delays. The mixed delays include constant delay in the leakage term (i.e., “leakage delay”), time-varying delays and continuously distributed delays. Based on the Lyapunov method and the linear matrix inequality (LMI) approach, some sufficient conditions ensuring global asymptotic stability of the equilibrium point are derived, which are dependent on both the discrete and distributed time delays. These conditions are expressed in terms of LMI and can be easily checked by MATLAB LMI toolbox. In addition, two numerical examples are given to illustrate the feasibility of the result. 相似文献
12.
This paper analyzes synchronization in finite time for two types of coupled delayed Cohen–Grossberg neural networks (CDCGNNs). In the first type, linearly coupled Cohen–Grossberg neural networks with and without coupling delays are considered, respectively. In the second type, nonlinearly coupled Cohen–Grossberg neural networks both with and without coupling delays are discussed. By designing suitable controllers and using some inequality techniques, several criteria ensuring finite-time synchronization of the CDCGNNs with linear coupling and nonlinear coupling are derived, respectively. Moreover, the settling times of synchronization in finite time for the considered networks are also predicted. In the end, the availability for the acquired finite-time synchronization conditions is confirmed by two selected numerical examples. 相似文献
13.
This paper investigates the global asymptotic stability of stochastic fuzzy Markovian jumping neural networks with mixed delays under impulsive perturbations in mean square. The mixed delays include constant delay in the leakage term (i.e., “leakage delay”), time-varying delay and continuously distributed delay. By using the Lyapunov functional method, reciprocal convex approach, linear convex combination technique, Jensen integral inequality and the free-weight matrix method, several novel sufficient conditions are derived to ensure the global asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed results, which do not require the differentiability and monotonicity of the activation functions, can be easily checked via Matlab software. Finally, two numerical examples are given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature. 相似文献
14.
This paper is concerned with the problem of global robust asymptotic stability for delayed neural networks with polytopic parameter uncertainties and time-varying delay. A delay-dependent and parameter-dependent robust stability criterion for the equilibrium of delayed neural networks in the face of polytopic type uncertainties is presented by using a parameter-dependent Lyapunov functional and taking the relationship between the terms in the Leibniz–Newton formula into account. This criterion, expressed as a set of linear matrix inequalities, requires no matrix variable to be fixed for the entire uncertainty polytope, which produces a less conservative stability result. 相似文献
15.
This paper is concentrated on exploring the exponential synchronization of reaction-diffusion coupled neural networks with fractional-order and impulses. Firstly, an extended Halanay-type inequality is established to cope with the hybrid delay-dependent impulsive problem by utilizing the mathematical induction. Furthermore, a direct error method is introduced by constructing Lyapunov function for the addressed networks to investigate the exponential synchronization under impulsive effects. By utilizing the technique of average impulsive interval and strength, some sufficient synchronization criteria are derived, which are closely associated with time delay and the commensurate order for fractional-order systems. Lastly, three numerical examples are presented to demonstrate the correctness for established results. 相似文献
16.
This paper is concerned with stability for aperiodic sampled-data systems. Firstly, for aperiodic sampled-data systems without uncertainties, a new Lyapunov-like functional is constructed by introducing the double integral of the derivative of the state, the integral of the state, and the integral of the cross term of the state and the sampled state. When estimating the derivative of the Lyapunov-like functional, superior integral inequalities to Jensen inequality are employed to get a tighter upper bound. By the Lyapunov-like functional principle, sampling-interval-dependent stability results are derived. Then, the stability results are extended to aperiodic sampled-data systems with polytopic uncertainties. Finally, some examples are listed to show the stability results have less conservatism than some existing ones. 相似文献
17.
《Journal of The Franklin Institute》2022,359(10):4915-4937
This paper is concerned with the aperiodically intermittent control (AIC) for the synchronization of discrete-time neural networks with time delay. The synchronization is analyzed by the piecewise Lyapunov function approach and the piecewise Lyapunov–Krasovskii functional approach, respectively. The average activation time ratio of AIC is estimated, which is more general and less conservative than the minimum activation time ratio. Finally, a numerical example is exploited and detailed comparisons are presented to demonstrate the effectiveness and less conservativeness of the obtained results. 相似文献
18.
Xinsong Yang Zunshui Cheng Xiaodi Li Tiedong Ma 《Journal of The Franklin Institute》2019,356(15):8138-8153
In this paper, new control scheme is considered for exponential synchronization of coupled neutral-type neural networks (NTNNs) with both bounded discrete-time delay and unbounded distributed delay (mixed delays). It is assumed that only the measured output can be utilized to design the controller. Quantized output controllers (QOCs) are considered to save the bits rate of communication channels and the bandwidth. The main difficulty in solving this problem is to cope with the neutral terms, the delays, and the uncertainties induced by the quantization simultaneously. By designing new Lyapunov–Krasovskii functionals and proposing novel analytical techniques, sufficient conditions are derived to ensure the exponential synchronization of the interested NTNNs. The control gains are given by solving a set of linear matrix inequalities (LMIs), which are not necessarily to be negative-definite matrices. Numerical examples are provided to verify the effectiveness and merits of the proposed approach. 相似文献
19.
《Journal of The Franklin Institute》2022,359(18):11108-11134
This paper focuses on the stochastic passivity problem of stochastic memristor-based complex valued neural networks with two different types of time-delays and reaction-diffusion terms by sampled-data control strategy. Different from the existing sampled-data strategies, this paper develops spatial and temporal point sampling, namely, only a finite number of points in space or time are sampled. By introducing two different Lyapunov functional and employing techniques such as Wirtinger’s integral inequality, Jensen’s inequality and Young’s inequality, etc., two different sufficient conditions for the stochastic passivity of the system are established. Prominently, the condition quantitatively reveals the relationship between the upper and lower bounds of the sampling interval at spatial and temporal points. Finally, a numerical example is given to verify the rationality of the proposed method. Notice, compared with a large number of results of real-valued reaction-diffusion neural networks, the research results of sampled-data controlled complex-valued reaction-diffusion neural networks have not appeared so far, and this work is the first attempt to fill in the gaps in this topic. 相似文献
20.
In this issue, the robust synchronization for a class of uncertain Cohen–Grossberg neural networks is studied, in which neuron activations are modelled by discontinuous functions(or piecewise continuous functions). Pinning state-feedback and adaptive controllers are designed to achieve global robust exponential synchronization and global robust asymptotical synchronization of drive-response-based discontinuous Cohen–Grossberg neural networks. By applying the theory of non-smooth analysis theory and the method of generalized Lyapunov functional, some criteria are given to show that the coupled discontinuous Cohen–Grossberg neural networks with parameter uncertainties can realized global robust synchronization. Some examples and numerical simulations are also shown to verify the validity of the proposed results. 相似文献