中文摘要：

网络层析成像将医学、地震学等领域成熟的层析成像理论应用于通信网络领域,它通过基于端到端测量来估计网络内部的行为,为目前在国际学术界备受关注的新技术之一.本文提出了一种基于递归多感知器网络（Recurrent Multilayer Perceptron：RMLP）延迟时变参数的追踪算法,该算法能够在没有任何先验信息条件下追踪非平稳网络链路平均延迟,估计链路延迟的概率密度分布.仿真实验也验证了以上两点,同时本文提出的算法比序贯蒙特卡洛（Sequential Monte Carlo：SMC）方法具有更小的估计误差.

英文摘要：

By applying tomography theory which is highly developed in fields such as medical computerized tomography and seismic tomography to communication network,network tomography has become one of the focused new technologies, which can infer the internal performance of the network by extemal end-to-end measurement. In this paper, we propose a novel Inference algorithm based on the recurrent multilayer perceptron（RMLP）network capable of tracking nonstationary network behavior and estimating time-varyihg,intemal delay characteristics.Simulation experiments demonstrate the performance of the RMLP network.