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基于样条权函数神经网络P2P流量识别方法
引用本文:侯善江,;张代远.基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014(7):21-24.
作者姓名:侯善江  ;张代远
作者单位:[1]南京邮电大学 计算机学院,江苏 南京210003; [2]南京邮电大学 计算机学院,江苏南京210003; [3]南京邮电大学计算机技术研究所,江苏南京210003
基金项目:江苏高校优势学科建设工程资助项目(yx002001)
摘    要:样条权函数神经网络是一种新兴的神经网络,克服了很多传统神经网络(如BP、RBF)的缺点:比如局部极小、收敛速度慢等。它具有拓扑结构简单,精确记忆训练过的样本,反映样本的信息特征,求得全局最小值等优点。基于这些优点,文中提出了一种基于样条权函数神经网络P2P流量识别方法。通过提取P2P流量特征,运用样条权函数神经网络结构对P2P流识别。Matlab仿真和模拟实验结果表明了这种方案的可行性,与传统神经网络相比,样条权函数神经网络在时间效率上具有明显优势。

关 键 词:样条权函数  神经网络  P2P  流量识别  插值

P2 P Traffic Identification Based on Spline Weight Function Neural Network
Affiliation:HOU Shan-jiang, ZHANG Dai-yuan ( 1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China; 2. Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China; 3. Institute of Computer Technology ,Nanjing University of Posts and Telecommunications ,Nanjing 210003 ,China)
Abstract:Spline weight function neural network is a new kind of neural network. It overcomes many defects of traditional neural networks ( like BP,RBF) ,such as local minima,slow convergence,at the same time has many advantages,such as simple structure,remembering trained samples,reflecting the characteristics of the sample information,finding global minima directly and so on. A method of P2P traffic identification based on spline weight function neural network is presented in this paper based on advantages of this neural network. The structure of spline weight function neural network can identify P2P traffic by extracting characteristics of P2P traffic training. Matlab sim-ulation and experimental results show the feasibility of the scheme. Compared with the traditional neural network,spline weight function neural network has obvious advantages in time efficiency.
Keywords:spline weight function  neural network  P2P  traffic identification  interpolation
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