Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Network topology and the theory of rubber elasticity

The earliest investigations on rubber elasticity, commencing in the 19th century, were necessarily limited to phenomenological interpretations. The realisation that polymers consist of very long molecular chains. commencing c. 1930, gave impetus to the molecular theory of rubber elasticity (1932-). according to which the high deformability of an elastomer, and the elastic force generated by deformation, stem from the configurations accessible to long molecular chains. Theories of rubber elasticity put forward from 1934-1946 relied on the assumption that the junctions of the rubber network undergo displacements that are affine in macroscopic strain. The theory of James and Guth (1947) dispensed with this premise, and demonstrated instead that the mean positions of the junctions of a ‘phantom’ network consisting of Gaussian chains devoid of material properties are affine in the strain. The vital significance of the distinction between the actual distribution of chain vectors in a network and their distribution if the junctions would be fixed at their mean positions went unnoticed for nearly 30 years. Experimental investigations, commencing with the incisive work of Gee in 1946. revealed large departures from the relationship of stress to strain predicted by the theories cited. This discrepancy prompted extensive studies, theoretical and experimental, during succeeding years. Inquiry into the fundamentals of polymer networks, formed for example by interlinking very long polymer molecules, exposed the need to take account of network imperfections, typically consisting of chains attached at only one end to a network junction. Various means were advocated to make corrections for these imperfections. The cycle rank ζ of the network has been shown (1976) to be the fundamental measure of its connectivity, regardless of the junction functionality and pattern of imperfections. Often overlooked is the copious interpenetration of the chains comprising typical elastomeric networks. Theories that attempt to represent such networks on a lattice are incompatible with this universal feature. Moreover, the dense interpenetration of chains may limit the ability of junctions in real networks to accommodate the fluctuations envisaged in the theory of phantom networks. It was suggested in 1975 that departures from the form predicted for the elastic equation of state are due to constraints on the fluctuations of junctions whose effect diminishes with deformation and with dilation. Formulation of a self-consistent theory based on this suggestion required recognition of the non-affine connection between the chain vector distribution function and the macroscopic strain in a real network, which may partake of characteristics of a phantom network in some degree. Implementation of the idea was achieved through postulation of domains of constraint affecting the equilibrium distribution of fluctuations of network junctions from their mean positions. This led in due course to a theory that accounts for the relationship of stress to strain virtually throughout the ranges of strain accessible to measurement. The theory establishes connections between structure and elastic properties. This is achieved with utmost frugality in arbitrary parameters.     

RanGen: A Random Network Generator for Activity-on-the-Node Networks

In this paper, we describe RanGen, a random network generator for generating activity-on-the-node networks and accompanying data for different classes of project scheduling problems. The objective is to construct random networks which satisfy preset values of the parameters used to control the hardness of a problem instance. Both parameters which are related to the network topology and resource-related parameters are implemented. The network generator meets the shortcomings of former network generators since it employs a wide range of different parameters which have been shown to serve as possible predictors of the hardness of different project scheduling problems. Some of them have been implemented in former network generators while others have not.     

基于网络环境的计算机资料室工作

随着信息技术的迅速发展,基于网络的信息资源共享已成为信息化社会的基本特征。数字化图书馆和电子期刊网的出现,正在改变着人们的阅读习惯,丰富的信息资源和跨时空的浏览方式彻底颠覆了传统的图书馆、资料室的服务模式。同时,数字化图书馆也给资料室管理模式创新带来了新的契机。分析了院系资料室面临的挑战与机遇,探讨了新形势下计算机资料室工作,提出了利用信息技术,改革服务方式,拓展服务内容,提高服务水平,提供有特色的专业服务。     

Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays

In this paper, we discuss average consensus problem in undirected networks of dynamic agents with fixed and switching topologies as well as multiple time-varying communication delays. By employing a linear matrix inequality method, we prove that all the nodes in the network achieve average consensus asymptotically for appropriate communication delays if the network topology is connected. Particularly, several feasible linear matrix inequalities are established to determine the maximal allowable upper bound of time-varying communication delays. Numerical examples are given to demonstrate the effectiveness and the sharpness of the theoretical results.     

A review on queueing network models with finite capacity queues for software architectures performance prediction

A review is carried out on how queueing network models with blocking have been applied so far into the performance evaluation and prediction of Software Architectures (SA). Queueing network models with finite capacity queues and blocking have recently been introduced and applied as more realistic models of systems with finite capacity resources and population constraints. Queueing network models have been often adopted as models for the evaluation of software performance. Starting from our own experience, we observe the need of a more accurate definition of the performance models of SA to capture some features of the communication systems. We consider queueing networks with finite capacity and blocking after service (BAS) to represent some synchronization constraints that cannot be easily modeled with queueing network models with infinite capacity queues. We investigate the use of queueing networks with blocking as performance models of SA with concurrent components and synchronous communication. Queueing theoretic analysis is used to solve the queueing network model and study the synchronous communication and performance of concurrent software components. Our experience is supported by other approaches that also propose the use of queueing networks with blocking. Directions for future research work in the field are included.     

Individual and structural origins of friendship and social position among professionals.

Friendship affects individual and organizational well-being through direct relations, social positions, and complex network structures. In this study, the authors use longitudinal data from 2 groups of master's of business administration students to increase understanding of how friendship networks develop. The authors propose and test a dynamic model in which attribute similarity facilitates dyadic friendship ties, as well as similar network centrality and social position; early friendship increases later similarity in structural position and centrality; and early structural similarity enhances the likelihood of future friendship. Findings largely supported the model, demonstrating how homophily and early social contacts can jointly shape maturing friendship networks. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

多级网络多处理机系统的性能评估

本文建立了多级网络(δ-网)多处理机系统的马尔柯夫模型,为系统结构参数和任务粒度的选择提供了依据。文中分析了处理机数目、网络结构参数和任务粒度对系统性能的影响,并对模型计算结果和仿真结果作了比较。     

神经网络分类器的快速构造算法

使用ＢＰ算法训练多层网络的速度很慢而且事先难于确定隐节点和隐层的适当数目。本文提出一个有效的算法，先构造决策树，然后将构造的决策树转换为神经网。文中使用一个全局准则函数控制决策树的增长，它较好地匹配了树的复杂性和训练样本量及错分率界。实验结果，本文的算法比用ＢＰ算法训练多层网络要快，而其分类精度不低于用ＢＰ算法训练的多层神经网。     

基于神经PID网络的串级调节系统研究

本文提出了一种神经PID网络控制器，并利用它构成串级调节系统。在给出网络结构和计算公式的基础上，进行了计算机仿真。仿真结果表明，神经PID网络控制器构成的串级调节系统具有良好的动态和静态性能及很强的抗扰能力。