Adaptive line enhancers on the basis of least-squares algorithm for a single sinusoid detection

Koji Matsuura, Eiji Watanabe, Akinori Nishihara

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


This paper proposes adaptive line enhancers with new coefficient update algorithms on the basis of least-square-error criteria. Adaptive algorithms by least-squares are known to converge faster than stochastic-gradient ones. However they have high computational complexity due to matrix inversion. To avoid matrix inversion the proposed algorithms adapt only one coefficient to detect one sinusoid. Both FIR and IIR types of adaptive algorithm are presented, and the techniques to reduce the influence of additive noise is described in this paper. The proposed adaptive line enhancers have simple structures and show excellent convergence characteristics. While the convergence of gradient-based algorithms largely depend on their stepsize parameters, the proposed ones are free from them.

Original languageEnglish
Pages (from-to)1536-1543
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number8
Publication statusPublished - 1999 Jan 1
EventProceedings of the 1998 13th Digital Signal Processing Symposium - Niigata, Jpn
Duration: 1998 Nov 121998 Nov 13

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


Dive into the research topics of 'Adaptive line enhancers on the basis of least-squares algorithm for a single sinusoid detection'. Together they form a unique fingerprint.

Cite this