Optimal order EDS and FEDS algorithms

Zhongkai Zhang, Tamal Bose, Jacob Gunther

Research output: Contribution to journalConference article

4 Scopus citations

Abstract

This paper is based on a recently published class of adaptive filtering algorithms, namely, the Euclidean Direction Search (EDS) algorithms. The computationally efficient version is called the Fast Euclidean Direction Search (FEDS) algorithm with a computational complexity of O(N). In this paper, we present two new algorithms called the Optimal Euclidean Direction Search (OEDS) and the Optimal Fast Euclidean Direction Search (OFEDS). The optimal algorithms search all the Euclidean directions in each iteration to find the direction giving the greatest decrease of the cost function. In order to reduce the computational complexity, some sub-optimal methods based on the same principle are also discussed. Computer simulation results illustrate that the optimal and suboptimal algorithms converge faster than the original EDS and FEDS algorithms, but achieve the same steady state mean square error.

Original languageEnglish (US)
Pages (from-to)1559-1563
Number of pages5
JournalConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2
StatePublished - Dec 1 2004
Externally publishedYes
EventConference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 7 2004Nov 10 2004

    Fingerprint

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this