时变时滞区间神经网络的全局鲁棒稳定性判据

本文主要研究时变时滞区间神经网络的全局鲁棒稳定性问题, 利用区间神经网络的等价转换和自由矩阵技术, 给出一个新的区间神经网络平衡点的时滞依赖全局鲁棒稳定性的充分条件, 这个条件以线性矩阵不等式的形式给出, 容易验证, 保守性低.最后, 通过数值实例验证了所提算法的正确性和更低的保守性.     

广义的时滞细胞神经网络的动态分析

本文研究了广义细胞神经网络的动态行为,首先利用度理论建立了客中广义时滞细胞神经网络的平衡点存在唯一物充要条件,其次给出这种广义时滞神经网络全局指数稳定的充要条件。     

具反映扩散无穷连续分布时滞神经网络的全局渐近稳定性

利用同伦不变性原理、Dini导数、格林公式,研究了一类具反应扩散的无穷时滞神经网络系统的平衡点的存在唯一性和全局渐近稳定性.在去掉对神经元的激励函数有界性、可微性、去掉对平均时滞∫∞0sk(s)ds有界性的要求,仅要求激励函数满足Lipchitz条件等较宽松的条件下,获得了该类系统的全局渐近稳定性的充分条件.改进和推广了已有文献的最新结果.并用实例说明了这些获得的结果的有效性.     

具比例时滞杂交双向联想记忆神经网络的全局指数稳定性

对一类具比例时滞杂交双向联想记忆神经网络进行研究,利用Brouwer不动点定理证明该网络的平衡点的存在唯一性.利用变换将具比例时滞杂交双向联想记忆神经网络变换成等价的具不等常时滞与变系数杂交双向联想记忆神经网络.利用不等式技巧建立一拟Halanay型不等式系统,进而得到了确保该系统全局指数稳定的时滞独立的充分条件.并给出两个算例验证所得结论的正确性.     

基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性

 研究了时变时滞Cohen-Grossberg神经网络的全局鲁棒稳定性问题.基于线性矩阵不等式技术,给出了保证时变时滞Cohen-Grossberg神经网络平衡点唯一性和全局鲁棒稳定性的新判据.这些新判据不依赖于时滞的大小和放大函数,且与现有的一些结果相比,具有易于验证、适用范围广、条件更不保守等特点.仿真结果验证了本文方法的有效性.     

具有参数摄动的时滞Hopfield神经网络的鲁棒稳定性分析及吸引域的估计

研究一类具有参数摄动的时滞Hopfield神经网络模型的鲁棒稳定性.应用Lyapunov泛函法,给出了平衡点渐近稳定的充分条件.利用矩阵范数的性质及线性矩阵不等式(LMI)理论,又得到了两个便于计算和验证的推论.提供了一种估计网络渐近稳定平衡点吸引域的方法,并详尽地分析了吸引域对神经网络实现联想记忆的影响.数值例子进一步证明了结论的有效性.     

具有参数摄动的时滞Hopfield神经网络的鲁棒稳定性

 研究一类具有参数摄动的时滞Hopfield神经网络模型的鲁棒稳定性.应用Lyapunov泛函法,给出了平衡点渐近稳定的充分条件.利用矩阵范数的性质及线性矩阵不等式(LMI)理论,又得到了两个便于计算和验证的推论.提供了一种估计网络渐近稳定平衡点吸引域的方法,并详尽地分析了吸引域对神经网络实现联想记忆的影响.数值例子进一步证明了结论的有效性.     

中立型时滞BAM神经网络的稳定性分析

文章介绍了中立型时滞BAM神经网络,并重点分析其稳定性,给出了中立型时滞BAM神经网络的平衡点唯一和全局指数稳定性的判据,同时举例说明判据的正确性和结果的有效性。     

基于LMI方法的时滞BAM神经网络的全局稳定性分析

对于时滞双向联想记忆(DBAM)神经网络的平衡点的稳定性问题,目前人们已经得到了很多富有意义的成果。该文提出一种新的神经网络模型标准神经网络模型(SNNM),通过状态的线性变换,将DBAM神经网络转化为时滞SNNM(DSNNM),并利用有关DSNNM的稳定性的一些结论,得到DBAM神经网络平衡点的全局渐近稳定性的充分条件。这些条件都以线性矩阵不等式(LMI)的形式给出,容易验证,保守性低。该方法扩展了以前的稳定性结果,同时也适用于其它类型的递归神经网络(时滞或非时滞)的稳定性分析。     

二阶Hopfield型神经网络的稳定性 分析及收敛速度的估计

本文讨论二阶连续Hopfield型神经网络平衡点的全局稳定性问题,利用LMI方法和Lyapunov方法得到了网络平衡点全局渐近稳定和全局指数稳定的几个充分条件,并对其指数收敛速度进行了估计.     

Qualitative analysis for recurrent neural networks with linear threshold transfer functions

Multistable networks have attracted much interest in recent years, since multistability is of primary importance for some applications of recurrent neural networks where monostability exhibits some restrictions. This paper focuses on the analysis of dynamical property for a class of additive recurrent neural networks with nonsaturating linear threshold transfer functions. A milder condition is derived to guarantee the boundedness and global attractivity of the networks. Dynamical properties of the equilibria of two-dimensional networks are analyzed theoretically, and the relationships between the equilibria features and network parameters (synaptic weights and external inputs) are revealed. In addition, the sufficient and necessary conditions for coexistence of multiple equilibria are obtained, which confirmed the observations in with a cortex-inspired silicon circuit. The results obtained in this paper are applicable to both symmetric and nonsymmetric networks. Simulation examples are used to illustrate the theory developed in this paper.     

New Results on Almost Periodic Solution of Shunting Inhibitory Cellular Neural Networks with Continuously Distributed Delays

In this paper,the existence,uniqueness and global attractivity are discussed on almost periodic solution of SICNNs（shunting inhibitory cellular neural networks）with continuously distributed delays.By using the fixed point theorem,differential inequality technique and Lyapunov functional method,giving the new ranges of parameters,several sufficient conditions are obtained to ensure the existence,uniqueness and global attractivity of almost periodic solution.Compared with the previous studies,our methods are more effective for almost periodic solution analysis of SICNNs with continuously distributed delays.Some existing results have been improved and extended.In order to show the effectiveness of the obtained results,an example is given in this paper.     

On the nonvanishing stability of undesirable equilibria for FIRGodard blind equalizers

The existence of undesirable equilibria of Godard (1980) or constant modulus algorithms (CMA) is demonstrated for all finite-dimensional FIR equalizers. Sufficient stability conditions are presented for these equilibria. It is shown that for the Godard-2 algorithm, these undesirable equilibria are locally stable as long as the equalizer length remains finite. Results indicate that merely increasing the equalizer length does not necessarily nullify the potential for local convergence by Godard algorithms     

Parameter-Dependent Lyapunov Function Method for a Class of Uncertain Nonlinear Systems with Multiple Equilibria

First, a new linear matrix inequality (LMI) characterization of extended strict positive realness is presented for linear continuous-time systems. Then a class of nonlinear systems with multiple equilibria subject to polytopic uncertainty is addressed by the parameter-dependent Lyapunov function method. New sufficient conditions for global convergence are presented. This allows the Lyapunov function to be parameter dependent. Furthermore, an LMI-based controller design method is also given, and reduced-order controllers can be designed by performing a structural constraint on the introduced slack variables. Several numerical examples are included to demonstrate the applicability of the proposed method.     

Some properties of solutions of the semi-state model for nonlinear nonstationary systems

Certain properties of solutions similar to set invariance, set attractivity, boundedness, BIBO stability, etc. are investigated for the semistate model $$P(t)\dot x = M(t,x)x + D(t,x)u,y = q(t,x,u).$$ For systems considered, it is assumed that the reduction to a normal form of lower order is not possible. Using the direct method of Liapunov, the properties of solutions are investigated without actual knowledge of solutions.     

Input and output coupled nonlinear systems

In this paper, a class of input and output coupled nonlinear systems with multiple equilibria are studied. These kinds of systems can also be viewed as interconnected systems composed of single-input and single-output systems through some linear and nonlinear interconnections. Frequency-domain conditions are established for global convergence and convergence of bounded solutions for such systems. The effects of nonlinear input and output interconnections can be studied through a nonsingular matrix. The design method based on linear matrix inequality for the interconnected matrix is presented. In addition, the relation between input and output coupling here and input transformation in control theory is established. The coupling method is illustrated through a coupled Chua's circuit. The nonexistence of chaotic attractors or limit cycles in the coupled Chua's circuit can be analyzed by convergence of bounded solutions.     

Global asymptotic and robust stability of recurrent neural networks with time delays

In this paper, two related problems, global asymptotic stability (GAS) and global robust stability (GRS) of neural networks with time delays, are studied. First, GAS of delayed neural networks is discussed based on Lyapunov method and linear matrix inequality. New criteria are given to ascertain the GAS of delayed neural networks. In the designs and applications of neural networks, it is necessary to consider the deviation effects of bounded perturbations of network parameters. In this case, a delayed neural network must be formulated as a interval neural network model. Several sufficient conditions are derived for the existence, uniqueness, and GRS of equilibria for interval neural networks with time delays by use of a new Lyapunov function and matrix inequality. These results are less restrictive than those given in the earlier references.     

Architecting noncooperative networks

In noncooperative networks users make control decisions that optimize their individual performance measure. Focusing on routing, two methodologies for architecting noncooperative networks are devised, that improve the overall network performance. These methodologies are motivated by problem settings arising in the provisioning and the run time phases of the network. For either phase, Nash equilibria characterize the operating point of the network. The goal in the provisioning phase is to allocate link capacities that lead to systemwide efficient Nash equilibria. The solution of such design problems is, in general, counterintuitive, since adding link capacity might lead to degradation of user performance. For systems of parallel links, it is shown that such paradoxes cannot occur and that the optimal solution coincides with the solution in the single-user case. Extensions to general network topologies are derived. During the run time phase, a manager controls the routing of part of the network flow. The manager is aware of the noncooperative behavior of the users and makes its routing decisions based on this information while aiming at improving the overall system performance. We obtain necessary and sufficient conditions for enforcing an equilibrium that coincides with the global network optimum, and indicate that these conditions are met in many cases of interest     

Experimental determination and thermodynamic calculation of the phase equilibria and surface tension in the Sn-Ag-In system

The phase equilibria of the Sn-Ag-In system were investigated by means of differential scanning calorimetry (DSC) and metallography. The isothermal sections at 180–600°C, as well as some vertical sections, were determined. Thermodynamic assessment of this system was also carried out based on the experimental data of thermodynamic properties and phase equilibria using the calculation of phase diagram (CALPHAD) method, in which the Gibbs energies of the liquid, fcc, and hcp phases are described by the subregular solution model, and those of compounds are represented by the sublattice model. The thermodynamic parameters for describing the phase equilibria were optimized, and reasonable agreement between the calculated and experimental results was obtained. The maximum bubble-pressure method and dilatometric method have been used in measurements of the surface tension and density of the binary In-Sn and ternary (Sn-3.8Ag)_eut + In (5 at.% and 10 at.%) liquid alloys, respectively. The experiments were performed in the temperature range from 160–930°C. The experimental data of the surface tension were compared with those obtained by the thermodynamic calculation of Butler’s model.