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41.
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
42.
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
43.
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
44.
运用Lyapunov函数方法,讨论了一维细胞神经网络模型的完全稳定性问题,给出了四组使模型具有完全稳定的充分条件. 相似文献
45.
现代优化计算方法在蛋白质结构预测中的应用 总被引:2,自引:1,他引:1
现代优化计算方法在蛋白质结构预测中占有重要地位.简要地介绍了模拟退火算法,遗传算法,人工神经网络和图论算法在蛋白质结构预测中的应用.对国内外近年来应用这些算法,特别是在蛋白质构象搜索问题中,解决蛋白质结构预测的研究作了回顾,并分析、比较了这几种算法的效果和特点. 相似文献
46.
Huseyin Ince 《Computational Management Science》2006,3(2):161-174
The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore,
it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare
with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven
non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock
Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain
this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks
overperform the SVR and time series model (GARCH). 相似文献
47.
48.
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
49.
50.
Xuyang Lou 《Journal of Mathematical Analysis and Applications》2007,328(1):316-326
In this paper, the problem of stochastic stability for a class of time-delay Hopfield neural networks with Markovian jump parameters is investigated. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. Without assuming the boundedness, monotonicity and differentiability of the activation functions, some results for delay-dependent stochastic stability criteria for the Markovian jumping Hopfield neural networks (MJDHNNs) with time-delay are developed. We establish that the sufficient conditions can be essentially solved in terms of linear matrix inequalities. 相似文献