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Paper
title

Performance Study of Partial Update Adaptive Filter Algorithms in Distributed Networks

Credit to Download: 1 | Page Numbers 4 | Abstract Views: 1413
Year: 2012
Present: شفاهي
COI code: ISCEE15_160
Paper Language: English

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Authors Performance Study of Partial Update Adaptive Filter Algorithms in Distributed Networks

Milad Khoshkhoo - Shahid Rajaee Teacher Training University, Faculty of Electrical and Computer Engineering, Tehran, Iran
Mohammad Moshtaghi -
  Mohammad Shams Esfand Abadi -

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 LeastMean Squares algorithms (SPU-NLMS) for distributed estimation problem based on incremental strategy in incremental network. The distributed SPU-NLMS (dSPUNLMS) reduce 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

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COI code: ISCEE15_160

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Khoshkhoo, Milad; Mohammad Moshtaghi & Mohammad Shams Esfand Abadi, 2012, Performance Study of Partial Update Adaptive Filter Algorithms in Distributed Networks, 15th Iranian Student Conference on Electrical Engineering, كاشان, سازمان علمي دانشجويي مهندسي برق كشور, https://www.civilica.com/Paper-ISCEE15-ISCEE15_160.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: (Khoshkhoo, Milad; Mohammad Moshtaghi & Mohammad Shams Esfand Abadi, 2012)
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