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51.
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 相似文献
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53.
P. J. C. Skitt M. A. Javed S. A. Sanders A. M. Higginson 《Journal of Intelligent Manufacturing》1993,4(1):79-94
The potential of using artificially simulated neural networks as intelligent, adaptive process-monitoring devices is discussed. The investigation is considered as a method for automatic, intelligent exception reporting for quality control applications. The technique is also compared with the conventional statistical approaches of principal component analysis and Kohonen's feature map. The applications of the technique in aerospace and manufacturing environments are presented and a possible extension of the method to incorporate a diagnostic function is discussed.Seconded from Cheltenham and Gloucester College of Higher Education as a Royal Society/SERC Research Fellow at Smith's Industries Aerospace and Defence Systems, Bishop's Cleeve, Cheltenham, UK. 相似文献
54.
Ying Tan 《The Journal of VLSI Signal Processing》2002,32(1-2):45-54
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. 相似文献
55.
Noel E. Sharkey 《Robotics and Autonomous Systems》1997,22(3-4):345-359
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. 相似文献
56.
57.
作者在本文中指出了吉比特网络的目标及其所带来的问题,采用了提出问题并回答问题(或说明可能答案)的方法来阐明。 相似文献
58.
Anna Hać 《Journal of Network and Systems Management》1994,2(1):49-62
This paper analyzes the performance of a switching architecture. The performance measures include the elapsed time of packet transfer and the waiting time to begin transfer. The architecture is partitioned depending on the type of network used and the expected traffic in the network. Every partition has a switch with a buffer that can absorb surges of bursty traffic within the network partition. The buffer size depends on the type of the network and incoming traffic. The partition size depends on the network bandwidth, network traffic, packet size and buffer size. Examples of different networks are used to show the applications of the model. The results show that the elapsed time of packet switch transfer depends exponentially on the number of partitions in the network. 相似文献
59.
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. 相似文献
60.
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. 相似文献