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21.
本文在A.Blanco等人的算法的基础上,提出了max-min神经网络的一种改进了的反馈学习算法,严格证明了该算法的迭代收敛性,理论分析及实例计算结果均表明,本文算法具有算法简单,收敛速度快,输出误差小等显著特点。 相似文献
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运输网络中最小饱和流的求解 总被引:4,自引:0,他引:4
运输网络中常常由于流量的不可控易发生堵塞现象.网络发生堵塞时的饱和流值达不到最大流值.最小饱和流是运输网络,尤其是紧急疏散网络设计中很重要的一个参数.通过建立网络的割集矩阵来确定网络的堵塞截面,基于此提出了求解最小饱和流的线性规划模型及算法.举例分析表明,利用该算法计算网络最小饱和流更加简便、更加实用. 相似文献
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戴伏生 《数学的实践与认识》2006,36(2):186-192
经典的D IJKSTRA和BELLM AN-F LOYD通信网络路由算法,只能根据特定网络参数得到最佳路由,却无法获得网络存在的全部可用路由,而通信网理论研究及网络管理等方面,往往需要获得节点之间的全部可用路由.研究出一种路由新算法,遵循逻辑代数运算规则、采用关联矩阵中行与行之间整合与删除方式计算,N个节点的网络只需N-1次整合及删除运算,就能得到源节点到任意节点两点之间全部路由结果.详细论证了算法的正确性与合理性,简介了算法的并行运算可行性及与经典路由算法的兼容性等问题.通过算例详细说明算法的计算过程,并验证其正确性. 相似文献
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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
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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
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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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