Logarithmic quantization in the least mean squares algorithm

被引:10
|
作者
Aldajani, Mansour A. [1 ]
机构
[1] King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi Arabia
关键词
adaptive filtering; efficient algorithms; least mean squares; sign algorithm; log-LMS; delta modulation; convergence analysis; implementation; power-of-two quantization;
D O I
10.1016/j.dsp.2007.04.014
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we introduce a framework for adaptive filtering techniques with simplified recursion. The simplification is mainly carried out by rounding the full-precision error information of the recursion to their closest power-of-two values. A new method for power-of-two quantization is proposed in this study. The method uses companded delta modulation structure to perform the quantization. The proposed structure shows a performance that is comparable to that of full precision adaptive filters. Convergence analysis of this structure is included and closed-form expressions for the error statistics are derived. Furthermore, an efficient method for implementing the new structure is presented where only simple shift and loop operations are required. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:321 / 333
页数:13
相关论文
共 50 条
  • [41] Loop-shaping techniques applied to the least-mean-squares algorithm
    Moir, T. J.
    [J]. SIGNAL IMAGE AND VIDEO PROCESSING, 2011, 5 (02) : 231 - 243
  • [42] A new approach to introducing a forgetting factor into the normalized least mean squares algorithm
    Nishiyama, Kiyoshi
    [J]. SIGNAL PROCESSING, 2015, 114 : 19 - 23
  • [43] The logarithmic least squares priority model of the collective IFNPRs
    Gong, Zai-Wu
    Bai, Ming-Guo
    Sun, Rui-Ling
    [J]. CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 5954 - +
  • [44] The logarithmic least squares and the generalized pseudoinverse in estimating ratios
    Kwiesielewicz, M
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1996, 93 (03) : 611 - 619
  • [45] Noisy FIR parameter estimation by combining of total least mean squares estimation and least mean squares estimation
    Lim, Jun-Seok
    [J]. IEICE ELECTRONICS EXPRESS, 2009, 6 (09): : 572 - 578
  • [46] ON THE TRACKING PERFORMANCE OF COMBINATIONS OF LEAST MEAN SQUARES AND RECURSIVE LEAST SQUARES ADAPTIVE FILTERS
    Nascimento, Vitor H.
    Silva, Magno T. M.
    Azpicueta-Ruiz, Luiz A.
    Arenas-Garcia, Jeronimo
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 3710 - 3713
  • [47] Convergence analysis of a twin-reference complex least-mean-squares algorithm
    Johansson, S
    Nordebo, S
    Claesson, I
    [J]. IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING, 2002, 10 (04): : 213 - 221
  • [48] Composite proportional normalized least mean squares adaptive algorithm for network echo cancellation
    Zoican, S
    [J]. ISSPA 2005: The 8th International Symposium on Signal Processing and its Applications, Vols 1 and 2, Proceedings, 2005, : 783 - 786
  • [49] The multiple reference principle component least mean squares algorithm: A projection based approach
    Nijsse, G
    Van Dijk, J
    Jonker, JB
    [J]. 2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL IV, PROCEEDINGS: AUDIO AND ELECTROACOUSTICS SIGNAL PROCESSING FOR COMMUNICATIONS, 2004, : 133 - 136
  • [50] A novel least mean squares algorithm for tracking a discrete-time fBm process
    Gupta, Anubha
    Joshi, ShivDutt
    [J]. 2006 ANNUAL IEEE INDIA CONFERENCE, 2006, : 217 - +