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【期刊论文】Research on Event Handling Models of Java
吴跃, WU Yue, WU Jing, ZHOU Ming-tian
Journal of Electronic Science and Technology of China Jun. 2004 Vol. 2 No.2,-0001,():
-1年11月30日
A new event-handling paradigm and its application model are proposed. The working mechanism and principle of event listener model is given in detail. Finally, the launching event mechanisms, the choosing event handling models and the dispatching mechanism are illustrated.
event hanlding models, event listener model, delegation model, dispatching
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17浏览
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【期刊论文】Global stability analysis on a class of cellular neural networks
吴跃, ZHANG Yi, YU Juebang & WU YUE
SCIENCE IN CHINA (Series E) February 2001 Vol. 44 No.1,-0001,():
-1年11月30日
The existence, uniqueness, globally exponential stability and speed of exponential con-vergence for a class of cellular neural networks are investigated. The existence of a unique equilibrium is proved under very concise conditions, and theorems for estimating the global convergence speed approaching the equilibrium and criteria for its globally exponential stability are derived, Considering synapse time delay, by constructing appropriate Lyapunov functional, the existence of a unique equilib-rium and its global stability for the delayed network are also proved. The results, which do not require the cloning template to be symmetric, are easy to use in network design.
celluar neural networks, equilibrium, complete stability, asymptotically global stability, expo-nential stability, synapse time delay
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28浏览
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54下载
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吴跃, 吴跃**, 邱会中, 余水, 余元辉
电子科技大学学报,2002,6(3):255-261,-0001,():
-1年11月30日
提出了一种基于Web数据库系统设计、实现和性能调优的新方法,该方法包括由RDBMS配置优化、应用模式设计优化和编程优化。通过内存、分段、磁盘参数和时间相关参数的优化可以设置一个好的RDBMS运行环境。在编程时,通过减少与后台连接和断开操作、建立和使用索引、多用存储过程和优化SQL语句可以优化系统性能。在应用设计时,通过优化应用逻辑和降低规范化可以大大地改善系统性能。
性能, 优化, Web数据库, 调优
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37浏览
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44下载
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【期刊论文】基于Multi-MobileAgent技术的个性化数据挖掘的研究
吴跃, 徐嘉莉
计算机应用,2004,7(7):1-3,-0001,():
-1年11月30日
文中提出了基于Multi-MobileAgent技术的个性化数据挖掘模型,介绍了该模型各个组成部分的功能,以及多个Agent之间如何相互协作完成个性化的数据挖掘,并给出了相关的算法。
数据挖掘, 多移动代理, 个性化
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55浏览
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【期刊论文】Global Convergence Analysis of a PCA Learning Algorithm
吴跃, Mao Ye, Yue Wu and Zhang Yi
,-0001,():
-1年11月30日
rincipal component analysis(PCA) by neural network is an adaptive statistical signal processing method which has many applications Since many PCA neural networks do not converge globally, it is nature to study the global convergence of PCA learning algorithm. In this paper, the previous works on the globally convergent PCA neural networks are presented first. Then based on the mismatch of previous PCA neural networks, we propose and analyze a PCA learning algorithm. This algorithm is convergent globally. And a rigorous mathematical proof is given. Simulation results show the efiiciency and effectiveness ofthis algorithm.
Principal component analysis, neural network, eigenvector, feature extraction
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28浏览
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36下载
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