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31.
A new method for constructing infinite families of k-tight optimal double loop networks 总被引:2,自引:0,他引:2
CHEN Xiebin Department of Mathematics Information Science Zhangzhou Teachers College Zhangzhou China 《中国科学A辑(英文版)》2006,49(4)
The double loop network (DLN) is a circulant digraph with n nodes and outdegree 2. DLN has been widely used in the designing of local area networks and distributed systems. In this paper, a new method for constructing infinite families of k-tight optimal DLN is presented. For k = 0,1,…,40, the infinite families of k-tight optimal DLN can be constructed by the new method, where the number nk(t,a) of their nodes is a polynomial of degree 2 in t and contains a parameter a. And a conjecture is proposed. 相似文献
32.
ZHANG Lin-bo LIU Xiao-hua JIANG Yuan GUO Ping SHA Li-jin LI Yu 《高等学校化学研究》2006,22(2):139-144
After establishing hemi-Parkinsonian rat models, the relationships between neuron death and the expression of several proteins, such as c-Fos, GFAP, GDNF, NF-κB and some cytokines were determined. Therapeutics experiments with notoginsenoside-Rg1 were carried out. The research results show that the expressions of GFAP, NF-Kκ and c-Fos will obviously increase in the lesion side of the striatum and the expression of GDNF will decrease, which implies that the signal transduction pathway may participate in the apoptosis in neurons. The levels of some cytokines such as TNF-α, IL-1β in the striatum of PD rat models increased compared to those of normal rats. The results of the therapeutics experiments show that notoginsenoside-Rg1 may repress the immune inflammation response and regulate the immune function through the neuro-immune molecular network. Therefore, notoginsenoside-Rg1 can be used as an effective drug for anti-oxidation and anti-inflammation, and can be used in the therapy of Parkinson's disease(PD). 相似文献
33.
Temperature effects on deposition rate of silicon nitride films were characterized by building a neural network prediction model. The silicon nitride films were deposited by using a plasma enhanced chemical vapor deposition system and process parameter effects were systematically characterized by 26−1 fractional factorial experiment. The process parameters involved include a radio frequency power, pressure, temperature, SiH4, N2, and NH3 flow rates. The prediction performance of generalized regression neural network was drastically improved by optimizing multi-valued training factors using a genetic algorithm. Several 3D plots were generated to investigate parameter effects at various temperatures. Predicted variations were experimentally validated. The temperature effect on the deposition rate was a complex function of parameters but N2 flow rate. Larger decreases in the deposition rate with the temperature were only noticed at lower SiH4 (or higher NH3) flow rates. Typical effects of SiH4 or NH3 flow rate were only observed at higher or lower temperatures. A comparison with the refractive index model facilitated a selective choice of either SiH4 or NH3 for process optimization. 相似文献
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A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination. 相似文献
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从大型复杂武器装备系统的具体特点出发,运用基于神经网络的评价方法,构建了大型复杂武器装备质量综合评价模型。实证分析的结果表明该方法得出的结果与实际情况相符。 相似文献
39.
四种多变量校准方法在FTIR多组分分析中的性能比较 总被引:1,自引:0,他引:1
本文对四种多变量校准方法--经典最小二乘法(CLS),偏最小二乘法(PLS),卡尔曼滤波法(KFM)以及人工神经网络法(ANN)--在多组分浓度分析方面的性能进行了比较。选择五种红外谱图严重混叠的大气有机毒物--1,3-丁二烯,苯,邻二甲苯,氯苯和丙烯醛--作为分析对象。分别计算各种方法对该5组分体系的平均预测误差MPE和平均相对误差MRE进行比较。结果表明,偏最小二乘法在处理这类问题中是最稳健的方法。 相似文献
40.
A transient molecular network model is built to describe the nonlinear viscoelasticity of polymers by considering the effect
of entanglement loss and regeneration on the relaxation of molecular strands. It is an extension of previous network theories.
The experimental data on three thermoplastic polymers (ABS, PVC and PA6) obtained under various loading conditions are used
to test the model. Agreement between the theoretical and experimental curves shows that the suggested model can describe successfully
the relaxation behavior of the thermoplastic polymers under different loading rates by using relatively few relaxation modes.
Thus the micromechanism responsible for strain-rate dependence of relaxation process and the origin of nonlinear viscoelasticity
may be disclosed.
The project supported by the National Natural Science Foundation of China and Doctorial Fund 相似文献