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Recurrent Neural Network Inference of Internal Delays in Nonstationary Data Network

  • Feng Qian
  • Guang-min Hu
  • Xing-miao Yao
  • Le-min Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

Abstract

By applying tomography theory which is highly developed in fieldssuchas 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 external 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-varying, internal delay characteristics. Simulation experiments demonstrate the performance of the RMLP network.

Keywords

Average Delay Recurrent Neural Network Digital Signal Processor Seismic Tomography Infinite Impulse Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Feng Qian
    • 1
  • Guang-min Hu
    • 1
  • Xing-miao Yao
    • 1
  • Le-min Li
    • 1
  1. 1.Key Lab of Broadband Optical Fiber Transmission and Communication NetworksUniversity of Electronic Science and Technology of ChinaChengduChina

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