Logarithmic quantization in the least mean squares algorithm

Mansour A. Aldajani*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)321-333
Number of pages13
JournalDigital Signal Processing: A Review Journal
Volume18
Issue number3
DOIs
StatePublished - May 2008

Bibliographical note

Funding Information:
The author would like to acknowledge the support of King Fahd University of Petroleum and Minerals for this work.

Keywords

  • Adaptive filtering
  • Convergence analysis
  • Delta modulation
  • Efficient algorithms
  • Implementation
  • Least mean squares
  • Log-LMS
  • Power-of-two quantization
  • Sign algorithm

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Applied Mathematics

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