具有时滞的高阶Hopfield型神经网络的稳定性

通过Lyapunov泛函的方法，对具有时滞的高阶连续型Hopfield神经网络平衡点的稳定性进行分析，利用Razumikhin定理得到平衡点全局一致渐近稳定的时滞相关与时滞无关充分条件。     

3—值逻辑函数的稳定性

本文提出了３－值逻辑函数稳定性的概念，考察“稳定”的概率定义，给出了３－值逻辑函数稳定的判别条件，提供了构造稳定的３－值逻辑函数的典型方法，用本文的方法，也可考察一般Ｐ－值逻辑函数的稳定性     

204弱噪声对单模染料激光器阈值行为的影响

２０４弱噪声对单模染料激光器阈值行为的影响张纪岳，周沧涛（西北大学）杨小丽，施卫（西安师专）（西安理工大学）在以往的染料激光研究中，人们主要利用在小噪声相关时间下，由泛函积分法或退耦合近似所得出的近似类Ｆ－Ｐ方程来研究单模染料激光模型的各种性质。本文...     

有间隙Ⅱ—Ⅵ族半导体材料散射特性的三维边缘元分析

用三维边缘元方法分析了有间隙Ⅱ－Ⅵ族半导体材料的散射特性，该方法直接从泛函变分出发避开了其它方法中示肯损超薄介质填充波导本征值和本片函数的困难，简化了求解过程，计算结果与实验值的比较证实了本方法具有有效，可靠和精确的特点。     

线性时滞系统的时滞相关稳定性

本文讨论了线性时滞系统x(t)=Ax( ) Bx(t-τ)渐近稳定的时滞界限，利用Lyapunov—Krasovskii泛函及H∞范数理论，获得了线性时滞系统时滞相关稳定的充分条件，同时得到了一个新的时滞界限的代数估计式。将本文结果应用于实际系统，计算简单，并且扩大了时滞的稳定区域，降低了对时滞的保守性。分析结果还表明，线性时滞系统的稳定性可以转化为一定常无时滞的线性系统的H∞控制问题。     

有间隙Ⅱ－Ⅵ族半导体材料散射特性的三维边缘元分析

用三维边缘元方法分析了有间隙Ⅱ－Ⅵ族半导体材料的散射特性．该方法直接从泛函变分出发，避开了其它方法中求解有损超薄介质填充波导本征值和本征函数的困难，简化了求解过程．计算结果与实验值的比较证实了本方法具有有效、可靠和精确的特点     

具有时滞的细胞神经网络的稳定性

该文研究了具有时滞的细胞神经网络的稳定性问题，运用Lyapunov泛函法和Razumikhin法分别给出了时滞细胞神经网络全局渐近稳定的两个新的充分条件，其中，第一个条件与时延无关，而第二个条件与时延有关，获得的定理推广了已有文献中的结果，对于时滞细胞神经网络的硬件设计具有一定的指导意义。     

线性时滞广义系统的时滞相关稳定性

本文研究了线性时滞广义系统的时滞相关稳定性。首先将该系统转化为一个带约束条件的中立型系统，然后利用Lyapunov-Krasovskii V泛函方法，利用Park不等式，获得了基于LMI的时滞相关稳定充分条件，该条件具有一般性，包含正常线性时滞系统作为其特例。最后的数值例子表明所得结论较已有文献具有较小的保守性。     

自适应有源噪声控制的滤波-LMAD算法

本文研究了稳定非高斯环境下的自适应有源噪声控制问题，提出了滤波－ＬＭＡＤ（ｌｅａｓｔｍｅａｎａｂｓｏｌｕｔｅｄｅｖｉａｔｉｏｎ）算法及归一化滤波－ＬＭＡＤ算法，仿真结果表明，与常用的滤波－ＬＭＳ算法和归－化滤波－ＬＭＳ算法相比，本文提出了算法收敛速度更快。     

参数不确定的单时滞系统基于简化的L-K泛函的稳定性分析

参数不确定和时滞广泛存在于各种实际的控制系统中,而且它们往往是导致系统不稳定或性能下降的原因。本文基于Lyapunov稳定性理论,通过构造简化的Lyapunov-Krasovskii泛函,同时应用线性矩阵不等式(LMI:linearmatrix inequality)方法,研究了参数不确定和单时变时滞系统的鲁棒稳定性问题,并导出了由LMI表示的该类系统的鲁棒稳定性判据,而且,通过这类简化的L-K泛函,在充分利用时滞信息的基础上减少了判据的保守性。最后借助含不确定性扰动的具有单时变时滞的单机-无穷大系统模型,分析了保持鲁棒稳定时系统可承受的最大时滞的界限,数值仿真验证了方法的有效性。     

On nonblocking switching networks for multichannel connections

This paper deals with switching networks for multichannel connections. The conditions under which the three-stage switching network is nonblocking for s-channel connections are given. Switching networks that are nonblocking in the strict sense as well as the switching networks nonblocking in the wide sense are considered. The conditions for two-sided and for one-sided switching networks are derived     

Chaos Synchronization in Complex Networks

In this paper, we study chaos synchronization in complex networks with time-invariant, time-varying and switching configurations based on the matrix measure of complex matrices. To begin with, we propose an analytical condition for chaos synchronization in complex networks with a time-invariant configuration. Secondly, we obtain some less conservative synchronization conditions for networks with a time-varying configuration. Thirdly, we consider chaos synchronization in networks with time-average and switching configurations. If complex subnetworks satisfy certain conditions, the networks with time-average and switching configurations are $M$-synchronizable. At last, we analyze the nonsynchronizability of complex networks. Chaos synchronization in complex networks can't be realized if the coupling configuration and the inner-coupling matrix satisfy certain conditions. Theoretical analysis and numerical simulations verify the effectiveness of the proposed synchronization criteria.      

非对称模板点格神经网络的动态特性研究

本文利用了矩阵Ｏｓｔｒｏｗｓｋｉ与ｂＲＡＵＥＲ对角占优之条件得到了点格神经网络平衡点存在的充分必要条件，然后利用Ｏｓｔｒｏｗｓｋｉ圆盘定理与Ｂｒａｕｅｒ卵形定理得到了点格神经网络的完全稳定性条件，这为非对称 模板的点格神经网络提出一和中新的研究方法。     

Global convergence of Lotka-Volterra recurrent neural networks with delays

Recurrent neural networks of the Lotka-Volterra model have been proven to possess characteristics which are desirable in some neural computations. A clear understanding of the dynamical properties of a recurrent neural network is necessary for efficient applications of the network. This paper studies the global convergence of general Lotka-Volterra recurrent neural networks with variable delays. The contributions of this paper are: 1) sufficient conditions are established for lower positive boundedness of the networks; 2) global exponential stability conditions are obtained for the networks. These conditions are totally independent of the variable delays which are therefore allowed to be uncertain; 3) novel Lyapunov functionals are constructed to establish delays dependent conditions for global asymptotic stability, and 4) simulation results and examples are provided to supplement and illustrate the theoretical contributions presented.     

Sufficient and necessary conditions for global exponential stability of discrete-time recurrent neural networks

A set of sufficient and necessary conditions are presented for global exponential stability (GES) of a class of generic discrete-time recurrent neural networks. By means of the uncovered conditions, GES and convergence properties of the neural networks are analyzed quantitatively. It is shown that exact equivalences exist among the GES property of the neural networks, the contractiveness of the deduced nonlinear operators, and the global asymptotic stability (GAS) of the neural networks plus the spectral radius of Jacobian matrix of the neural networks at the unique equilibrium point less than one. When the neural networks have small state feedback coefficients, it is shown further that the infimum of exponential bounds of the trajectories of the neural networks equals exactly the spectral radius of Jacobian matrix of the neural networks at the unique equilibrium point. The obtained results are helpful in understanding essence of GES and clarifying difference between GES and GAS of the discrete-time recurrent neural networks.     

Energy Efficiency of Heterogeneous Networks in LTE-Advanced

Traditionally mobile operators have met the surge in mobile data traffic and the growing number of rural subscribers by deploying more macro base stations. This increases overall energy consumption, operational costs and carbon footprint of cellular networks. In this paper we investigate solutions for reducing the number and size of active macrocells following traffic load conditions in both homogeneous and heterogeneous networks. Results are presented as overall energy reduction gains for homogeneous macro-only and micro-only networks and heterogeneous joint macro-relay and micro-relay networks, using long-term-evolution-advanced technology. Results show that reducing the number of active cells using sleep mode at base stations, in low to medium traffic load conditions, combined with the deployment of small cells offer energy gains in both homogeneous and heterogeneous networks. However, the most significant gains are observed in heterogeneous networks.     

移动本地传输网ASON部署策略

文章首先描述了移动本地传输网的建设目标,然后结合目前移动本地传输网的现状介绍了在移动本地传输网中引入自动交换光网络(ASON)技术需要的各种条件,提出了在现有移动本地网基础上如何部署ASON,并提出了传统同步数字体系(SDH)网络和ASON的混合组网方案.     

Rearrangeable one-sided switching networks composed of uniform time-space elements

One-sided rearrangeable switching networks composed of uniform time-space elements are considered. Two theorems presenting conditions under which two- and four-wire networks are rearrangeable are given and proven. These theorems are also applicable for multiple-linkage space-division switching networks.     

Electromagnetic Interference Reduction Filters

This paper presents the theory and application of lumped-image parameter reactive filter networks, absorptive-type filter networks, and combined absorptive-reactive filter networks as conducted electromagnetic interference reduction circuits. A comparison of the passband characteristics by specific examples is given for filter configurations of the pi, T, absorptive, and absorptive-reactive type under implementation conditions of a fixed source impedance and a varying load impedance as encountered when filtering prime power sources feeding ac to dc converters. This paper illustrates the problem the design engineer faces when applying the usual data given in filter catalogs. The filter characteristics are presented for 50-ohm resistive source and load conditions because of MIL-STD-220A quality control testr equirements. A test configuration is recommended to determine the admittance transfer of a filter network, indicative of the networks performance characteristics under application conditions.     

动态分布参数神经网络时空稳定性分析

本文将Hopfield自联想神经网络和Kosko异联想神经网络推广到无穷维状态空间动态神经网络,即动态分布参数神经网络,并给出了它们的有界性和稳定性。尤其是还研究了带微分算子的多维分布参数神经网络的时空稳定性以及保证稳定情况下所应满足的边界条件。最后,还给出了一个应用实例。