图象矢量量化——改进的竞争学习算法  

The Traffic Estimation of Common Signalling Network

作　　者：孙复君[1] 阮传概[1] 

机构地区：[1]北京邮电大学信息工程系

出　　处：《北京邮电大学学报》1997年第3期85-88,共4页Journal of Beijing University of Posts and Telecommunications

摘　　要：用神经网络实现图象矢量量化是一种非常有效的方法．在对竞争学习算法（ＣＬ）和频率敏感竞争学习算法（ＦＳＣＬ）分析的基础上，提出了一种改进的竞争学习算法（ＭＣＬ），实验表明，ＭＣＬ算法优于ＣＬ算法和ＦＳＣＬ算法．The conceptual model for CCS network are presented.It is described how to introduce the traffic growth factors in CCS network from the traffic growth factors in message network. It contains the traffic growth factors between signalling end points and traffic growth factors of signalling link set. The method for signalling traffic forecasting and computation method are considered.

关 键 词：图象处理 矢量量化 神经网络 

分 类 号：TN919.8[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]