Spin probe study of semi‐interpenetrating polymer networks based on polyurethane and polymethacrylate functional prepolymers

The motional transition and heterogeneity of semi‐interpenetrating networks (SIPNs) based on polyurethane (PU) with carboxylic groups and methacrylic copolymer (PM) with tertiary amine groups were studied by the electron spin resonance (ESR) spin probe method. The concentration of functional groups in both prepolymers varied from 0 to 0.45 mmol g^?1. Spin‐probed SIPNs show that the temperature‐dependent spectra are sensitive to polymer interactions imposed by functional groups. These interactions determine the free volume distribution in the matrix and temperature at which motional transition takes place. The fraction of free volume increases with functional group concentration and reaches its maximum at 0.25 mmol g^?1. Further increases in the functional group concentration reduce the free volume. The results of the networks with strong interactions are discussed in terms of the interference of the plasticizing effect of the PU component and the formation of possible cluster cross‐links, which restricts segmental motions. Copyright © 2003 Society of Chemical Industry     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

精细功能陶瓷的若干发展趋势

概括了分析自９０年代初以来精细功能陶瓷的发展趋势，提出了一些相关的研究领域。     

Polymer networks based on α,ω-methacrylate-terminated poly(1,3-dioxolane)

α,ω-Methacrylate-terminated poly(1,3-dioxolane)s (polyDXL) were synthesized by cationic ring-opening polymerization of DXL in the presence of methylene-bis(oxyethylmethacrylate) as transfer agent. If the initiator concentration is small compared with the transfer agent concentration, the molecular weights of the polymers are governed by the ratio of the reacted monomer to the reacted transfer agent. The α,ω-methacrylate-terminated polyDXLs obtained undergo free radical polymerization with formation of polyacetal networks. The properties of the networks as function of the molecular weight of the corresponding prepolymers are reported.     

Mixed Mode VLSI Implementation of a Neural Associative Memory

A mixed mode digital/analog special purpose VLSI hardware implementation of an associative memory with neural architecture is presented. The memory concept is based on a matrix architecture with binary storage elements holding the connection weights. To enhance the processing speed analog circuit techniques are applied to implement the algorithm for the association. To keep the memory density as high as possible two design strategies are considered. First, the number of transistors per storage element is kept to a minimum. In this paper a circuit technique that uses a single 6-transistor cell for weight storage and analog signal processing is proposed. Second, the device precision has been chosen to a moderate level to save area as much as possible. Since device mismatch limits the performance of analog circuits, the impact of device precision on the circuit performance is explicitly discussed. It is shown that the device precision limits the number of rows activated in parallel. Since the input vector as well as the output vector are considered to be sparsely coded it is concluded, that even for large matrices the proposed circuit technique is appropriate and ultra large scale integration with a large number of connection weights is feasible.     

Dynamical considerations of network properties

Elasticity is discussed as an aspect of viscoelasticity, which is described by the tube model. The effects of both crosslinks and entanglements contribute to this model and a discussion of how these effects can be quantified is given. At high enough concentration, entanglements ensure the existence of elastic effects even without crosslinks, and a theory is presented on how this dynamical phase change comes about.     

宽带无源光网络(BPON)关键技术的发展与研究

宽带无源光网络（BPON）是实现宽带、多业务接入的理想物理平台，本文介绍了BPON网络的发展，重点讨论了将ATM技术和PON技术相结合的APON系统及其升级系统SuperPON的基本结构和关键技术，对最近兴起的将以太技术和PON技术相结合的EPON系统的基本概念和工作原理也进行了阐述，并对未来BPON技术的发展进行了展望。     

基于规则的光学邻近矫正中规则的相关处理

讨论了如何选择适当的规则,如何建立简洁实用的规则库,如何应用规则库.提出了四种主要的光学邻近矫正规则,在实验结果中列举了规则库中的部分数据.利用规则矫正后的版图光刻得到的硅片图形有了明显的改善.规则库的自动建立部分 (OPCL)是基于规则的光学邻近矫正系统的重要组成部分.     

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