Partial update conjugate gradient algorithms for adaptive filtering

Bei Xie, Tamal Bose

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In practice, computational complexity is an important consideration of an adaptive signal processing system. A well-known approach to controlling computational complexity is applying partial update (PU) adaptive filters. In this paper, a partial update conjugate gradient (CG) algorithm is employed. Theoretical analyses of mean and mean-square performance are presented. The simulation results of different PU CG algorithms are shown. The performance of PU CG algorithms are also compared with PU recursive least squares (RLS) and PU Euclidean direction search (EDS) algorithms.

Original languageEnglish (US)
Title of host publicationPECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems
Pages317-323
Number of pages7
StatePublished - Sep 12 2011
Externally publishedYes
Event1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011 - Vilamoura, Algarve, Portugal
Duration: Mar 5 2011Mar 7 2011

Publication series

NamePECCS 2011 - Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems

Other

Other1st International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2011
CountryPortugal
CityVilamoura, Algarve
Period3/5/113/7/11

Keywords

  • Conjugate gradient adaptive filter
  • Partial update
  • Recursive algorithms

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Communication

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