Multi-stage adaptive signal processing algorithms

S. S. Kozat, A. C. Singer

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


In this paper, we explore the use of multi-stage adaptation algorithms for a variety of adaptive filtering applications where the structure of the underlying process to be estimated is unknown. These algorithms are "multi-stage" in that they comprise multiple adaptive filtering algorithms that operate in parallel on the observation sequence, and adaptively combine the outputs of this first stage to form an overall signal estimate. Several examples of this class of algorithms are demonstrated and analyzed in both a deterministic and stochastic context with respect to their convergence and mean squared error. The first example of this class, a "universal" linear predictor, was recently introduced and shown to asymptotically achieve the performance of the best linear predictor for each sequence, (up to some maximal order). Two new algorithms have been developed that generalize this universal linear predictor, and explore the use of the LMS algorithm in each stage of adaptation. Each of these algorithms are compared through theoretical analysis of their behavior.

Original languageEnglish (US)
Title of host publicationProceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2000
PublisherIEEE Computer Society
Number of pages5
ISBN (Electronic)0780363396
StatePublished - 2000
EventIEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2000 - Cambridge, United States
Duration: Mar 16 2000Mar 17 2000

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)2151-870X


OtherIEEE Sensor Array and Multichannel Signal Processing Workshop, SAME 2000
Country/TerritoryUnited States


  • Adaptive filters
  • Adaptive signal processing
  • Algorithm design and analysis
  • Convergence
  • Data compression
  • Filtering algorithms
  • Least squares approximation
  • Machine learning algorithms
  • Resonance light scattering
  • Signal processing algorithms

ASJC Scopus subject areas

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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