A spherical subspace based adaptive filter

  • Authors:

  • Eric M. Dowling;Ronald D. DeGroat

  • Affiliations:

  • Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX;Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, Richardson, TX

  • Venue:
  • ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: digital speech processing - Volume III
  • Year:
  • 1993

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Abstract

In this paper, we use the adaptation mechanism of the spherical subspace tracker together with the weighting scheme of Total Least Squares (TLS) to construct an adaptive filter that tracks solutions to time varying ordinary least squares, total least squares, data least squares, and reduced rank total least squares problems. To study convergence properties, we relate our filter to Thompson's constrained stochastic gradient eigenfilter. We present a convergence rate acceleration scheme to keep the filter from being slowed down by saddle points in the performance surface. Simulation results verify the theoretical development.