首页> 外文OA文献 >Entropy minimization based robust algorithm for adaptive networks Uyarlamali aǧlar i̇çi̇n entropi̇ mi̇ni̇mi̇zasyonuna dayali gürbüz bi̇r algori̇tma
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Entropy minimization based robust algorithm for adaptive networks Uyarlamali aǧlar i̇çi̇n entropi̇ mi̇ni̇mi̇zasyonuna dayali gürbüz bi̇r algori̇tma

机译:基于熵最小化的自适应网络鲁棒算法基于自适应网络熵迁移的鲁棒算法

摘要

In this paper, the problem of estimating the impulse responses of individual nodes in a network of nodes is dealt. It was shown by the previous work in literature that when the nodes can interact with each other, fusion based adaptive filtering approaches are more effective than handling nodes independently. Here we are proposing the use of entropy functional based optimization in the adaptive filtering stage. We tested the new method on networks under Gaussian and ε-contaminated Gaussian noise. The results show that the proposed method achieves significant improvements in the error rates in case of ε-contaminated noise. © 2012 IEEE.
机译:在本文中,解决了估计节点网络中各个节点的脉冲响应的问题。文献中的先前工作表明,当节点可以彼此交互时,基于融合的自适应过滤方法比独立处理节点更有效。在这里,我们提出在自适应滤波阶段使用基于熵函数的优化。我们在高斯和ε污染的高斯噪声下的网络上测试了该新方法。结果表明,该方法在ε噪声污染的情况下,在错误率方面取得了显着改善。 ©2012 IEEE。

著录项

  • 作者

    Kose K.; Cetin A.E.; Gunay O.;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 tur
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