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An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification

An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification
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摘要 In this paper after analyzing the adaptation process of the proportionate normalized least mean square(PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefcient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity. In this paper after analyzing the adaptation process of the proportionate normalized least mean square (PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive filter coefficient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead stage with much less computational complexity.
出处 《Journal of Shanghai Jiaotong university(Science)》 EI 2013年第6期742-748,共7页 上海交通大学学报(英文版)
关键词 adaptive algorithm echo cancellation(EC) proportionate normalized least mean square(PNLMS) algorithm proportionate step-size sparse impulse response adaptive algorithm, echo cancellation (EC), proportionate normalized least mean square (PNLMS)algorithm, proportionate step-size, sparse impulse response
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  • 1BENESTY J, GANSLER T, MORGAN D R, et al. Advances in network and acoustic echo cancellation: Digital signal processing [M]. New York: Springer, 2001.
  • 2ITU-T Recommendation G.168, Digital network echo cancellers [S].
  • 3宫延伟,吉小军,黄峰一,阮晓虹.Fast Affine Projection Algorithm for Adaptive Noise Canceling and Its Application on the Fetal Electrocardiogram Extraction[J].Journal of Shanghai Jiaotong university(Science),2009,14(6):690-694. 被引量:1
  • 4BERSHAD N J, BIST A. Fast coupled adaptation for sparse impulse responses using a partial Haar trans-form [J]. IEEE Transactions on Signal Procesing, 2005, 53(3): 966-976.
  • 5DUTTWEILER D L. Subsampling to estimate delay with application to echo cancelling [J]. IEEE Transactions on Acoustic, Speech and Signal Processing, 1983, 31(5): 1090-1099.
  • 6Ho K C, BLUNT S D. Adaptive sparse system identification using wavelets [J]. IEEE Transactions on Cir-cuits and Systems - II: Analog and Digital Signal Processing, 2002, 49(10): 656-667.
  • 7Ho K C, BLUNT S D. Rapid Identification of a sparse impulse response using an adaptive algorithm in the Haar domain [J]. IEEE Transactions on Signal Procesing, 2003, 51(3): 628-638.
  • 8DUTTWEILER D L. Proportionate normalized least mean squares adaptation in echo cancelers [J]. IEEE Transactions on Speech and Audio Processing, 2000, 8(5): 508-518.
  • 9GAY S L, LUCENT B L. An efficient, fast converging adaptive filter for network echo cancellation [C]/ / Conference Record of the Thirty-Second Asilomar Conference on Signals, System and Computers. Pacific Grove, CA, USA: IEEE, 1998: 394-398.
  • 10NEKUII M, ATARODI M. A fast converging algorithm for network echo cancellation [J]. IEEE Signal Processing Letters, 2004, 11(4): 427-430.

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