Estimation of a signal waveform from noisy data using low-rankapproximation to a data matrix

  • Authors:
  • D.W. Tufts;A.A. Shah

  • Affiliations:
  • Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 1993

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Abstract

An analysis and improvement of a data-adaptive signal estimation algorithm are presented. Perturbation analysis of a reduced-rank data matrix is used to reveal its statistical properties. The obtained information is used for calculating the performance of the Toeplitz-restoration algorithm of D. Tufts et al. (1982). This analysis leads to improvements of the methods, and the predicted improvements are demonstrated by simulation and comparison with the Cramer-Rao bounds