Subspace-Based Rational Interpolation of Analytic Functions From Phase Data

Akcay H.

IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol.58, no.3, pp.1069-1081, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 3
  • Publication Date: 2010
  • Doi Number: 10.1109/tsp.2009.2033326
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1069-1081
  • Keywords: Phase data, rational interpolation, strong consistency, subspace-based identification, time-delay estimation, FREQUENCY-RESPONSE DATA, DOMAIN POWER SPECTRA, SYSTEM-IDENTIFICATION, APPROXIMATION
  • Anadolu University Affiliated: No


In this paper, two simple subspace-based identification algorithms to identify stable linear-time-invariant systems from corrupted phase samples of frequency response function are developed. The first algorithm uses data sampled at nonuniformly spaced frequencies and is strongly consistent if corruptions are zero-mean additive random variables with a known covariance function. However, this algorithm is biased when corruptions are multiplicative, yet it exactly retrieves finite-dimensional systems from noise-free phase data using a finite amount of data. The second algorithm uses phase data sampled at equidistantly spaced frequencies and also has the same interpolation and strong consistency properties if corruptions are zero-mean additive random variables. The latter property holds also for the multiplicative noise model provided that some noise statistics are known a priori. Promising results are obtained when the algorithms are applied to simulated data.