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Information Journal Paper

Title

PERFORMANCE ANALYSIS OF SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARES ALGORITHM OVER AN ADAPTIVE INCREMENTAL NETWORK

Pages

  85-92

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 algorithm (SPU-NLMS) for DISTRIBUTED ESTIMATION problem in an INCREMENTAL NETWORK. The distributed SPU-NLMS (dSPU-NLMS) has close convergence speed to dNLMS, low steady-state mean square error (MSE), and low computational complexity features. In addition, the mean-square performance analysis of dSPU-NLMS algorithm for each individual node is presented. The theoretical expressions for stability bounds, transient and steady-state performance analysis of dSPU-NLMS are introduced. The validity of the theoretical results and the good performance of dSPU-NLMS are demonstrated by several computer simulations.

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  • Cite

    APA: Copy

    ESFAND ABADI, MOHAMMAD SHAMS, DANAEE, ALI REZA, & SEIFOURI, MAHMOOD. (2012). PERFORMANCE ANALYSIS OF SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARES ALGORITHM OVER AN ADAPTIVE INCREMENTAL NETWORK. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), 11(2), 85-92. SID. https://sid.ir/paper/283521/en

    Vancouver: Copy

    ESFAND ABADI MOHAMMAD SHAMS, DANAEE ALI REZA, SEIFOURI MAHMOOD. PERFORMANCE ANALYSIS OF SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARES ALGORITHM OVER AN ADAPTIVE INCREMENTAL NETWORK. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)[Internet]. 2012;11(2):85-92. Available from: https://sid.ir/paper/283521/en

    IEEE: Copy

    MOHAMMAD SHAMS ESFAND ABADI, ALI REZA DANAEE, and MAHMOOD SEIFOURI, “PERFORMANCE ANALYSIS OF SELECTIVE PARTIAL UPDATE NORMALIZED LEAST MEAN SQUARES ALGORITHM OVER AN ADAPTIVE INCREMENTAL NETWORK,” IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), vol. 11, no. 2, pp. 85–92, 2012, [Online]. Available: https://sid.ir/paper/283521/en

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