Published in: 20th Iranian Conference on Electric Engineering
COI code: ICEE20_342
Paper Language: English
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Authors SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARE ALGORITHMS FOR DISTRIBUTED ESTIMATION OVER AN ADAPTIVE INCREMENTAL NETWORKMohammad Shams Esfand Abadi - Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
Ali-Reza Danaee -
Abstract:Selective partial update (SPU) strategy in adaptive filter algorithms is used to reduce the computational complexity. In this paper we apply the SPU Normalized Least Mean Squares algorithms (SPU-NLMS) for distributed estimation problem based on incremental strategy in a incremental network. The distributed SPU-NLMS (dSPUNLMS) reduces the computational complexity while it’s performance is close to the dNLMS. We demonstrate the good performance of dSPU-NLMS in both convergence speed and steady-state mean square error
Keywords:Selective partial update, normalized least mean squares, distributed estimation, incremental network
COI code: ICEE20_342
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Esfand Abadi, Mohammad Shams & Ali-Reza Danaee, 2012, SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARE ALGORITHMS FOR DISTRIBUTED ESTIMATION OVER AN ADAPTIVE INCREMENTAL NETWORK, 20th Iranian Conference on Electric Engineering, تهران, دانشگاه تهران, https://www.civilica.com/Paper-ICEE20-ICEE20_342.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Esfand Abadi, Mohammad Shams & Ali-Reza Danaee, 2012)
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